Creator · rlaope
Last updated · Sep 2, 2026
[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, r
Creator · rlaope
Last updated · Sep 2, 2026
[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, r
Creator · rlaope
Last updated · Sep 2, 2026
[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, r
Creator · rlaope
Last updated · Sep 2, 2026
[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, r
Review then install
Install targets
Codex install prompt
Install the "omh-adversarial-consensus" agent skill from https://github.com/rlaope/oh-my-hermes/tree/main/skills/omh-adversarial-consensus. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"rlaope-omh-adversarial-consensus","task":"Install omh-adversarial-consensus","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.3K
78/100 Quality · 84/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.3K GitHub stars
Repo activity
1.3K stars, 125 forks
Maintenance
4d since push
License
MIT
Install
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusDo not use when
Alternative
1.9K Stars
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Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
Agent should check
Copy prompt
Task: Use omh-adversarial-consensus in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install
Install command: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
LLM text format
/api/skills/rlaope-omh-adversarial-consensus/install?format=text
Find alternatives
/api/skills/search?q=omh-adversarial-consensus&limit=3
Agent prompt
Use omh-adversarial-consensus for this task. Review https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install, then install with: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/rlaope-omh-adversarial-consensus
LLM text
/api/registry/manifest/rlaope-omh-adversarial-consensus?format=text
Install alias
/api/registry/install/rlaope-omh-adversarial-consensus
Recommend
/api/registry/recommend?task=Use%20omh-adversarial-consensus%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.3K GitHub stars
Stars/forks activity
INFO1.3K stars, 125 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: "omh-adversarial-consensus" description: "[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives." metadata: hermes: tags: [workflow, oh-my-hermes, planning] category: planning phase: adversarial-consensus role: planner quality_tier: reviewed-plan-gated ---
# Adversarial Consensus
This is a Hermes-native `adversarial-consensus` workflow skill.
## Why This Exists
`adversarial-consensus` exists because agreement reached by perspectives that read each other is not review — it is convergence. Independent findings, an attack round nobody is allowed to defend against, and a distillation that may only subtract produce objections a single planning pass never surfaces, and the mandatory handoff keeps that bundle from being mistaken for the plan.
## Do Not Use When
- The user wants the plan itself, with options, acceptance criteria, and verification commands; use `ralplan`, which this workflow feeds. - The request is still too ambiguous to state the proposal being attacked; use `deep-interview` first. - The user wants completed code reviewed for defects rather than a proposal attacked before it is built; use `code-review`. - The user wants hostile runtime scenarios against a built change; use `ultraqa`. - One perspective would do: a small local change with no contested decision does not earn three rounds.
## Examples
Good example:
- Prompt: $adversarial-consensus we plan to move session state into Redis before the launch — attack it from every angle before I write the plan. - Expected behavior: Name the roster and their distinct angles, take blind findings from each, run one attack-only round, resolve each objection to defend/refine/concede, distill only into the four buckets, and hand the bundle to `ralplan` as planning input. - Why: The decision is contested and pre-plan, which is exactly where independent objections are worth more than one planner's confidence.
Bad example:
- Prompt: $adversarial-consensus give me the migration plan with the steps and the rollout order. - Expected behavior: Produce the distilled bundle and hand it to `ralplan`; the steps and rollout order are the planner's output, not this workflow's. - Why: The bundle is INPUT to planning. Emitting a plan here skips the reviewed-plan gate and turns the buckets into a task list.
## Completion Checklist
- The roster is named with 3-5 distinct angles, and no two seats argue the same one. - Round-one findings were produced blind, and any perspective that could not be kept blind is named as a broken-independence caveat instead of being presented as independent. - Every cross-attack objection targets another perspective's finding, and no perspective defended itself in that round. - Every objection carries exactly one verdict — defended, refined, or conceded — and conceded findings are struck, not softened. - The bundle contains only Hard Constraints, Decisions, Risks, Open Questions, every line traces to a surviving finding, and nothing new was added at distillation. - The closing message states that the bundle is input, names the follow-on planning workflow, and claims no plan, acceptance, implementation, or verification evidence.
## Recovery Notes
- If the proposal under review cannot be stated in one paragraph, route back to `deep-interview` before opening round one. - If independence was broken — a perspective saw another's findings, or the same seat produced two angles — say so, re-run that perspective on a restated problem, and mark the round's independence as caveated rather than silently continuing. - If a round produces no objections at all, treat that as a roster defect rather than consensus: state which angle is missing and add or replace a seat before distilling. - If distillation would need a fifth bucket, the extra content is a plan trying to escape; move it to the planner handoff instead of widening the bucket set.
## Workflow Lane
- Current lane: **Intent -> plan** (`oh-my-hermes`, `meta-router`, `deep-interview`, `context`, `plan`, `ralplan`, `adversarial-consensus`, `codebase-onboarding`, `+7 more`) - clarify, plan, ship, or loop goals. - If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.
## Use When
Use when a proposal, plan, or direction needs independent perspectives to attack it before a plan is written, and the distilled result is meant as input to planning rather than as the plan.
Strong routing signals: `adversarial-consensus`, `$adversarial-consensus`, `adversarial planning`, `adversarial plan review`, `red team this plan`, `red-team this plan`, `red team the proposal`, `multi-perspective review`, `multiple perspectives`, `independent perspectives`, `attack this proposal`, `poke holes in this`, `hyperplan`, `敵対的レビュー`, `多角的レビュー`, `レッドチームレビュー`, `この計画に反論`, `穴を探して`, `적대적 검토`, `다관점 검토`, `여러 관점에서 검토`, `레드팀 검토`, `이 계획 반박`, `허점 찾아`, `对抗式评审`, `多视角评审`, `红队评审`, `反驳这个方案`, `找出漏洞`
## Catalog Metadata
Category: `planning` Phase: `adversarial-consensus` Hermes role: `planner` Quality tier: `reviewed-plan-gated` Reasoning demand: `standard`
Quality bar:
- Name the roster before round one: 3-5 perspectives, each with a stated angle that no other seat covers. The suggested roster is skeptic, validator, researcher, architect, creative; substitute a domain seat when the problem needs one, but two seats arguing the same angle is a duplicate, not a perspective. - Run the rounds in order — independent findings; cross-attack; defend, refine, or concede — and state which round is active in every message, because the independence rule and the no-self-defense rule only mean anything relative to the current round. Load `references/consensus-protocol.md` for the per-round procedure, the per-seat angle table, and the failure modes that make a run look adversarial while producing agreement. - Round one is blind: each perspective produces findings without seeing any other perspective's output, and each finding names its evidence or labels itself an assumption. - Round two attacks only: every perspective attacks other perspectives' findings and never defends or restates its own. A perspective with no objection to any other seat says so explicitly rather than filling the round with agreement. - Round three answers each objection with exactly one verdict — defend with evidence, refine the finding, or concede it — and a conceded finding is struck from the record instead of being softened. - The lead distills only. Nothing new enters at distillation: every line in the bundle traces to a surviving finding, and it goes into one of Hard Constraints, Decisions, Risks, Open Questions — never into a fifth bucket, a recommendation, a sequence of steps, or a task list. - End with the mandatory handoff: state that the bundle is INPUT to planning, name the follow-on planning workflow (`ralplan` for a reviewed plan, `plan` when the shape is already agreed), and stop. Treating the bundle as the plan is the anti-pattern this workflow exists to prevent. - Keep round transitions and perspective outputs as declarations: a stated round change is not evidence that the round happened, and a distilled bundle is not plan acceptance, implementation, review, CI, or merge evidence.
Handoff policy:
Keep every round in Hermes as prepared prompt contracts. The distilled bundle is planning input: hand it to `ralplan` or `plan` for the plan itself, and prepare a selected executor/runtime handoff only after that separate planning pass produces an accepted plan.
Required inputs:
- the proposal, plan draft, or direction under review - the decision the review must inform - known constraints and non-negotiables - the perspective roster and why each angle is distinct
Expected outputs:
- per-perspective independent findings - cross-attack objections attributed to their author - defend, refine, or concede verdict per objection - distilled bundle in the fixed buckets Hard Constraints, Decisions, Risks, Open Questions - mandatory planner handoff naming the follow-on planning workflow
Artifact expectations:
- record the distilled bundle with `omh hermes plan --record`, which writes `<repo>/.omh/plans/<slug>.md` inside a repository and the user-scope OMH store outside one, so the planner pass consumes a file rather than scrollback
Safety rules:
- Do not write the plan here. This workflow produces the input a planner consumes, never the plan itself. - Do not let a perspective read another perspective's findings before its own are recorded; a perspective that saw the others is not an independent objection. - Do not let a perspective defend its own findings during the cross-attack round; that round attacks other perspectives only. - Do not add, rename, or drop a distillation bucket; the closed set is Hard Constraints, Decisions, Risks, Open Questions. - Do not invent evidence on behalf of a perspective; an unsupported objection is recorded as an Open Question, not as a Hard Constraint. - Do not report a round transition, a perspective's output, or the distilled bundle as executed, reviewed, or accepted work; every phase output is a declaration until the user or a wrapper observes it.
## Runtime Evidence
Preferred harness for this skill: `planning`.
```sh omh runtime record --skill adversarial-consensus --harness planning --status started ```
Record observed delegation results; otherwise return `not_available` or `not_observed`. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence. - Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion.
Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.
Shared product, compatibility, topology, memory, harness, and execution rules: `omh-routing/references/skill-common-rail.md`. Load it when applicable; otherwise name an unavailable capability.
Source provenance
Decision snapshot
1,309 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for omh-adversarial-consensus, ready for a manual X post.
omh-adversarial-consensus: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then... 1.3K stars https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x
Listing + install path for omh-adversarial-consensus: https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x Install: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Listing source
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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@rlaope
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
mono-color
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Install targets
Codex install prompt
Install the "omh-adversarial-consensus" agent skill from https://github.com/rlaope/oh-my-hermes/tree/main/skills/omh-adversarial-consensus. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"rlaope-omh-adversarial-consensus","task":"Install omh-adversarial-consensus","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.3K
78/100 Quality · 84/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.3K GitHub stars
Repo activity
1.3K stars, 125 forks
Maintenance
4d since push
License
MIT
Install
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusDo not use when
Alternative
1.9K Stars
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Alternative
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Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
Agent should check
Copy prompt
Task: Use omh-adversarial-consensus in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install
Install command: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
LLM text format
/api/skills/rlaope-omh-adversarial-consensus/install?format=text
Find alternatives
/api/skills/search?q=omh-adversarial-consensus&limit=3
Agent prompt
Use omh-adversarial-consensus for this task. Review https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install, then install with: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/rlaope-omh-adversarial-consensus
LLM text
/api/registry/manifest/rlaope-omh-adversarial-consensus?format=text
Install alias
/api/registry/install/rlaope-omh-adversarial-consensus
Recommend
/api/registry/recommend?task=Use%20omh-adversarial-consensus%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.3K GitHub stars
Stars/forks activity
INFO1.3K stars, 125 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: "omh-adversarial-consensus" description: "[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives." metadata: hermes: tags: [workflow, oh-my-hermes, planning] category: planning phase: adversarial-consensus role: planner quality_tier: reviewed-plan-gated ---
# Adversarial Consensus
This is a Hermes-native `adversarial-consensus` workflow skill.
## Why This Exists
`adversarial-consensus` exists because agreement reached by perspectives that read each other is not review — it is convergence. Independent findings, an attack round nobody is allowed to defend against, and a distillation that may only subtract produce objections a single planning pass never surfaces, and the mandatory handoff keeps that bundle from being mistaken for the plan.
## Do Not Use When
- The user wants the plan itself, with options, acceptance criteria, and verification commands; use `ralplan`, which this workflow feeds. - The request is still too ambiguous to state the proposal being attacked; use `deep-interview` first. - The user wants completed code reviewed for defects rather than a proposal attacked before it is built; use `code-review`. - The user wants hostile runtime scenarios against a built change; use `ultraqa`. - One perspective would do: a small local change with no contested decision does not earn three rounds.
## Examples
Good example:
- Prompt: $adversarial-consensus we plan to move session state into Redis before the launch — attack it from every angle before I write the plan. - Expected behavior: Name the roster and their distinct angles, take blind findings from each, run one attack-only round, resolve each objection to defend/refine/concede, distill only into the four buckets, and hand the bundle to `ralplan` as planning input. - Why: The decision is contested and pre-plan, which is exactly where independent objections are worth more than one planner's confidence.
Bad example:
- Prompt: $adversarial-consensus give me the migration plan with the steps and the rollout order. - Expected behavior: Produce the distilled bundle and hand it to `ralplan`; the steps and rollout order are the planner's output, not this workflow's. - Why: The bundle is INPUT to planning. Emitting a plan here skips the reviewed-plan gate and turns the buckets into a task list.
## Completion Checklist
- The roster is named with 3-5 distinct angles, and no two seats argue the same one. - Round-one findings were produced blind, and any perspective that could not be kept blind is named as a broken-independence caveat instead of being presented as independent. - Every cross-attack objection targets another perspective's finding, and no perspective defended itself in that round. - Every objection carries exactly one verdict — defended, refined, or conceded — and conceded findings are struck, not softened. - The bundle contains only Hard Constraints, Decisions, Risks, Open Questions, every line traces to a surviving finding, and nothing new was added at distillation. - The closing message states that the bundle is input, names the follow-on planning workflow, and claims no plan, acceptance, implementation, or verification evidence.
## Recovery Notes
- If the proposal under review cannot be stated in one paragraph, route back to `deep-interview` before opening round one. - If independence was broken — a perspective saw another's findings, or the same seat produced two angles — say so, re-run that perspective on a restated problem, and mark the round's independence as caveated rather than silently continuing. - If a round produces no objections at all, treat that as a roster defect rather than consensus: state which angle is missing and add or replace a seat before distilling. - If distillation would need a fifth bucket, the extra content is a plan trying to escape; move it to the planner handoff instead of widening the bucket set.
## Workflow Lane
- Current lane: **Intent -> plan** (`oh-my-hermes`, `meta-router`, `deep-interview`, `context`, `plan`, `ralplan`, `adversarial-consensus`, `codebase-onboarding`, `+7 more`) - clarify, plan, ship, or loop goals. - If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.
## Use When
Use when a proposal, plan, or direction needs independent perspectives to attack it before a plan is written, and the distilled result is meant as input to planning rather than as the plan.
Strong routing signals: `adversarial-consensus`, `$adversarial-consensus`, `adversarial planning`, `adversarial plan review`, `red team this plan`, `red-team this plan`, `red team the proposal`, `multi-perspective review`, `multiple perspectives`, `independent perspectives`, `attack this proposal`, `poke holes in this`, `hyperplan`, `敵対的レビュー`, `多角的レビュー`, `レッドチームレビュー`, `この計画に反論`, `穴を探して`, `적대적 검토`, `다관점 검토`, `여러 관점에서 검토`, `레드팀 검토`, `이 계획 반박`, `허점 찾아`, `对抗式评审`, `多视角评审`, `红队评审`, `反驳这个方案`, `找出漏洞`
## Catalog Metadata
Category: `planning` Phase: `adversarial-consensus` Hermes role: `planner` Quality tier: `reviewed-plan-gated` Reasoning demand: `standard`
Quality bar:
- Name the roster before round one: 3-5 perspectives, each with a stated angle that no other seat covers. The suggested roster is skeptic, validator, researcher, architect, creative; substitute a domain seat when the problem needs one, but two seats arguing the same angle is a duplicate, not a perspective. - Run the rounds in order — independent findings; cross-attack; defend, refine, or concede — and state which round is active in every message, because the independence rule and the no-self-defense rule only mean anything relative to the current round. Load `references/consensus-protocol.md` for the per-round procedure, the per-seat angle table, and the failure modes that make a run look adversarial while producing agreement. - Round one is blind: each perspective produces findings without seeing any other perspective's output, and each finding names its evidence or labels itself an assumption. - Round two attacks only: every perspective attacks other perspectives' findings and never defends or restates its own. A perspective with no objection to any other seat says so explicitly rather than filling the round with agreement. - Round three answers each objection with exactly one verdict — defend with evidence, refine the finding, or concede it — and a conceded finding is struck from the record instead of being softened. - The lead distills only. Nothing new enters at distillation: every line in the bundle traces to a surviving finding, and it goes into one of Hard Constraints, Decisions, Risks, Open Questions — never into a fifth bucket, a recommendation, a sequence of steps, or a task list. - End with the mandatory handoff: state that the bundle is INPUT to planning, name the follow-on planning workflow (`ralplan` for a reviewed plan, `plan` when the shape is already agreed), and stop. Treating the bundle as the plan is the anti-pattern this workflow exists to prevent. - Keep round transitions and perspective outputs as declarations: a stated round change is not evidence that the round happened, and a distilled bundle is not plan acceptance, implementation, review, CI, or merge evidence.
Handoff policy:
Keep every round in Hermes as prepared prompt contracts. The distilled bundle is planning input: hand it to `ralplan` or `plan` for the plan itself, and prepare a selected executor/runtime handoff only after that separate planning pass produces an accepted plan.
Required inputs:
- the proposal, plan draft, or direction under review - the decision the review must inform - known constraints and non-negotiables - the perspective roster and why each angle is distinct
Expected outputs:
- per-perspective independent findings - cross-attack objections attributed to their author - defend, refine, or concede verdict per objection - distilled bundle in the fixed buckets Hard Constraints, Decisions, Risks, Open Questions - mandatory planner handoff naming the follow-on planning workflow
Artifact expectations:
- record the distilled bundle with `omh hermes plan --record`, which writes `<repo>/.omh/plans/<slug>.md` inside a repository and the user-scope OMH store outside one, so the planner pass consumes a file rather than scrollback
Safety rules:
- Do not write the plan here. This workflow produces the input a planner consumes, never the plan itself. - Do not let a perspective read another perspective's findings before its own are recorded; a perspective that saw the others is not an independent objection. - Do not let a perspective defend its own findings during the cross-attack round; that round attacks other perspectives only. - Do not add, rename, or drop a distillation bucket; the closed set is Hard Constraints, Decisions, Risks, Open Questions. - Do not invent evidence on behalf of a perspective; an unsupported objection is recorded as an Open Question, not as a Hard Constraint. - Do not report a round transition, a perspective's output, or the distilled bundle as executed, reviewed, or accepted work; every phase output is a declaration until the user or a wrapper observes it.
## Runtime Evidence
Preferred harness for this skill: `planning`.
```sh omh runtime record --skill adversarial-consensus --harness planning --status started ```
Record observed delegation results; otherwise return `not_available` or `not_observed`. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence. - Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion.
Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.
Shared product, compatibility, topology, memory, harness, and execution rules: `omh-routing/references/skill-common-rail.md`. Load it when applicable; otherwise name an unavailable capability.
Source provenance
Decision snapshot
1,309 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for omh-adversarial-consensus, ready for a manual X post.
omh-adversarial-consensus: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then... 1.3K stars https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x
Listing + install path for omh-adversarial-consensus: https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x Install: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Listing source
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
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@rlaope
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
mono-color
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1.9K StarsLast30days Skill
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61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsReview then install
Install targets
Codex install prompt
Install the "omh-adversarial-consensus" agent skill from https://github.com/rlaope/oh-my-hermes/tree/main/skills/omh-adversarial-consensus. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"rlaope-omh-adversarial-consensus","task":"Install omh-adversarial-consensus","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.3K
78/100 Quality · 84/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.3K GitHub stars
Repo activity
1.3K stars, 125 forks
Maintenance
4d since push
License
MIT
Install
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
Agent should check
Copy prompt
Task: Use omh-adversarial-consensus in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install
Install command: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
LLM text format
/api/skills/rlaope-omh-adversarial-consensus/install?format=text
Find alternatives
/api/skills/search?q=omh-adversarial-consensus&limit=3
Agent prompt
Use omh-adversarial-consensus for this task. Review https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install, then install with: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/rlaope-omh-adversarial-consensus
LLM text
/api/registry/manifest/rlaope-omh-adversarial-consensus?format=text
Install alias
/api/registry/install/rlaope-omh-adversarial-consensus
Recommend
/api/registry/recommend?task=Use%20omh-adversarial-consensus%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.3K GitHub stars
Stars/forks activity
INFO1.3K stars, 125 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: "omh-adversarial-consensus" description: "[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives." metadata: hermes: tags: [workflow, oh-my-hermes, planning] category: planning phase: adversarial-consensus role: planner quality_tier: reviewed-plan-gated ---
# Adversarial Consensus
This is a Hermes-native `adversarial-consensus` workflow skill.
## Why This Exists
`adversarial-consensus` exists because agreement reached by perspectives that read each other is not review — it is convergence. Independent findings, an attack round nobody is allowed to defend against, and a distillation that may only subtract produce objections a single planning pass never surfaces, and the mandatory handoff keeps that bundle from being mistaken for the plan.
## Do Not Use When
- The user wants the plan itself, with options, acceptance criteria, and verification commands; use `ralplan`, which this workflow feeds. - The request is still too ambiguous to state the proposal being attacked; use `deep-interview` first. - The user wants completed code reviewed for defects rather than a proposal attacked before it is built; use `code-review`. - The user wants hostile runtime scenarios against a built change; use `ultraqa`. - One perspective would do: a small local change with no contested decision does not earn three rounds.
## Examples
Good example:
- Prompt: $adversarial-consensus we plan to move session state into Redis before the launch — attack it from every angle before I write the plan. - Expected behavior: Name the roster and their distinct angles, take blind findings from each, run one attack-only round, resolve each objection to defend/refine/concede, distill only into the four buckets, and hand the bundle to `ralplan` as planning input. - Why: The decision is contested and pre-plan, which is exactly where independent objections are worth more than one planner's confidence.
Bad example:
- Prompt: $adversarial-consensus give me the migration plan with the steps and the rollout order. - Expected behavior: Produce the distilled bundle and hand it to `ralplan`; the steps and rollout order are the planner's output, not this workflow's. - Why: The bundle is INPUT to planning. Emitting a plan here skips the reviewed-plan gate and turns the buckets into a task list.
## Completion Checklist
- The roster is named with 3-5 distinct angles, and no two seats argue the same one. - Round-one findings were produced blind, and any perspective that could not be kept blind is named as a broken-independence caveat instead of being presented as independent. - Every cross-attack objection targets another perspective's finding, and no perspective defended itself in that round. - Every objection carries exactly one verdict — defended, refined, or conceded — and conceded findings are struck, not softened. - The bundle contains only Hard Constraints, Decisions, Risks, Open Questions, every line traces to a surviving finding, and nothing new was added at distillation. - The closing message states that the bundle is input, names the follow-on planning workflow, and claims no plan, acceptance, implementation, or verification evidence.
## Recovery Notes
- If the proposal under review cannot be stated in one paragraph, route back to `deep-interview` before opening round one. - If independence was broken — a perspective saw another's findings, or the same seat produced two angles — say so, re-run that perspective on a restated problem, and mark the round's independence as caveated rather than silently continuing. - If a round produces no objections at all, treat that as a roster defect rather than consensus: state which angle is missing and add or replace a seat before distilling. - If distillation would need a fifth bucket, the extra content is a plan trying to escape; move it to the planner handoff instead of widening the bucket set.
## Workflow Lane
- Current lane: **Intent -> plan** (`oh-my-hermes`, `meta-router`, `deep-interview`, `context`, `plan`, `ralplan`, `adversarial-consensus`, `codebase-onboarding`, `+7 more`) - clarify, plan, ship, or loop goals. - If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.
## Use When
Use when a proposal, plan, or direction needs independent perspectives to attack it before a plan is written, and the distilled result is meant as input to planning rather than as the plan.
Strong routing signals: `adversarial-consensus`, `$adversarial-consensus`, `adversarial planning`, `adversarial plan review`, `red team this plan`, `red-team this plan`, `red team the proposal`, `multi-perspective review`, `multiple perspectives`, `independent perspectives`, `attack this proposal`, `poke holes in this`, `hyperplan`, `敵対的レビュー`, `多角的レビュー`, `レッドチームレビュー`, `この計画に反論`, `穴を探して`, `적대적 검토`, `다관점 검토`, `여러 관점에서 검토`, `레드팀 검토`, `이 계획 반박`, `허점 찾아`, `对抗式评审`, `多视角评审`, `红队评审`, `反驳这个方案`, `找出漏洞`
## Catalog Metadata
Category: `planning` Phase: `adversarial-consensus` Hermes role: `planner` Quality tier: `reviewed-plan-gated` Reasoning demand: `standard`
Quality bar:
- Name the roster before round one: 3-5 perspectives, each with a stated angle that no other seat covers. The suggested roster is skeptic, validator, researcher, architect, creative; substitute a domain seat when the problem needs one, but two seats arguing the same angle is a duplicate, not a perspective. - Run the rounds in order — independent findings; cross-attack; defend, refine, or concede — and state which round is active in every message, because the independence rule and the no-self-defense rule only mean anything relative to the current round. Load `references/consensus-protocol.md` for the per-round procedure, the per-seat angle table, and the failure modes that make a run look adversarial while producing agreement. - Round one is blind: each perspective produces findings without seeing any other perspective's output, and each finding names its evidence or labels itself an assumption. - Round two attacks only: every perspective attacks other perspectives' findings and never defends or restates its own. A perspective with no objection to any other seat says so explicitly rather than filling the round with agreement. - Round three answers each objection with exactly one verdict — defend with evidence, refine the finding, or concede it — and a conceded finding is struck from the record instead of being softened. - The lead distills only. Nothing new enters at distillation: every line in the bundle traces to a surviving finding, and it goes into one of Hard Constraints, Decisions, Risks, Open Questions — never into a fifth bucket, a recommendation, a sequence of steps, or a task list. - End with the mandatory handoff: state that the bundle is INPUT to planning, name the follow-on planning workflow (`ralplan` for a reviewed plan, `plan` when the shape is already agreed), and stop. Treating the bundle as the plan is the anti-pattern this workflow exists to prevent. - Keep round transitions and perspective outputs as declarations: a stated round change is not evidence that the round happened, and a distilled bundle is not plan acceptance, implementation, review, CI, or merge evidence.
Handoff policy:
Keep every round in Hermes as prepared prompt contracts. The distilled bundle is planning input: hand it to `ralplan` or `plan` for the plan itself, and prepare a selected executor/runtime handoff only after that separate planning pass produces an accepted plan.
Required inputs:
- the proposal, plan draft, or direction under review - the decision the review must inform - known constraints and non-negotiables - the perspective roster and why each angle is distinct
Expected outputs:
- per-perspective independent findings - cross-attack objections attributed to their author - defend, refine, or concede verdict per objection - distilled bundle in the fixed buckets Hard Constraints, Decisions, Risks, Open Questions - mandatory planner handoff naming the follow-on planning workflow
Artifact expectations:
- record the distilled bundle with `omh hermes plan --record`, which writes `<repo>/.omh/plans/<slug>.md` inside a repository and the user-scope OMH store outside one, so the planner pass consumes a file rather than scrollback
Safety rules:
- Do not write the plan here. This workflow produces the input a planner consumes, never the plan itself. - Do not let a perspective read another perspective's findings before its own are recorded; a perspective that saw the others is not an independent objection. - Do not let a perspective defend its own findings during the cross-attack round; that round attacks other perspectives only. - Do not add, rename, or drop a distillation bucket; the closed set is Hard Constraints, Decisions, Risks, Open Questions. - Do not invent evidence on behalf of a perspective; an unsupported objection is recorded as an Open Question, not as a Hard Constraint. - Do not report a round transition, a perspective's output, or the distilled bundle as executed, reviewed, or accepted work; every phase output is a declaration until the user or a wrapper observes it.
## Runtime Evidence
Preferred harness for this skill: `planning`.
```sh omh runtime record --skill adversarial-consensus --harness planning --status started ```
Record observed delegation results; otherwise return `not_available` or `not_observed`. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence. - Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion.
Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.
Shared product, compatibility, topology, memory, harness, and execution rules: `omh-routing/references/skill-common-rail.md`. Load it when applicable; otherwise name an unavailable capability.
Source provenance
Decision snapshot
1,309 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for omh-adversarial-consensus, ready for a manual X post.
omh-adversarial-consensus: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then... 1.3K stars https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x
Listing + install path for omh-adversarial-consensus: https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x Install: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
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@rlaope
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mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
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Run autonomous deep research over web and local sources
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Install targets
Codex install prompt
Install the "omh-adversarial-consensus" agent skill from https://github.com/rlaope/oh-my-hermes/tree/main/skills/omh-adversarial-consensus. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {"event_id":"install_<unique-id>","skill_slug":"rlaope-omh-adversarial-consensus","task":"Install omh-adversarial-consensus","agent":"codex","outcome":"success","install_used":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.Supply asset profile
Deep research, source comparison, literature review, RAG, knowledge search, and reports.
Scenario
Research agents
I need my agent to research a topic, compare sources, and produce a concise report.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Maintenance
fresh
4d since push
Risk
Needs review
Financial research output is not financial advice; require human review before any live investment decision
GitHub quality
1.3K
78/100 Quality · 84/100 Trust
Coverage tags
Review notes
Financial research output is not financial advice; require human review before any live investment decision · Financial research output is not financial advice; require human review before any live investment decision.
Agent adoption scorecard
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
StrongSolid option that is likely worth shortlisting for production workflows.
Trust
Review then installGood shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Use as the primary candidate after human or sandbox review.
Stars
1.3K GitHub stars
Repo activity
1.3K stars, 125 forks
Maintenance
4d since push
License
MIT
Install
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Install safety
Agent-readable metadata
Use this block or the embedded JSON to decide whether an agent should install this skill, choose an alternative, or ask for human review first.
Suited tasks
Suited agents
Install decision
Trust and risk
Outcome loop
Install command
npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusDo not use when
Alternative
1.9K Stars
npx skills add yanliudesign/mono-color-skill --skill mono-color
Alternative
61.0K Stars
npx skills add mvanhorn/last30days-skill -g
Alternative
38.4K Stars
npx skills add Imbad0202/academic-research-skills
Alternative
28.0K Stars
npx skills add assafelovic/gpt-researcher
Agent safety v2
Usable candidate, but the agent should surface permission and audit notes before installation.
Require human approval before installing into a real workspace.
medium
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Skill may read or write project files, documents, generated artifacts, or local workspace state.
medium
Skill may inspect schemas, query databases, or work with persistent stores.
Agent resolve plan
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Open JSON
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
Agent should check
Copy prompt
Task: Use omh-adversarial-consensus in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20omh-adversarial-consensus%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install
Install command: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/rlaope-omh-adversarial-consensus/install
LLM text format
/api/skills/rlaope-omh-adversarial-consensus/install?format=text
Find alternatives
/api/skills/search?q=omh-adversarial-consensus&limit=3
Agent prompt
Use omh-adversarial-consensus for this task. Review https://www.openagentskill.com/api/skills/rlaope-omh-adversarial-consensus/install, then install with: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensusRegistry metadata
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/rlaope-omh-adversarial-consensus
LLM text
/api/registry/manifest/rlaope-omh-adversarial-consensus?format=text
Install alias
/api/registry/install/rlaope-omh-adversarial-consensus
Recommend
/api/registry/recommend?task=Use%20omh-adversarial-consensus%20in%20an%20agent%20workflow&limit=3
Agent fit
Local desktop
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Use this as a leading candidate, then validate the README and install path in your own agent stack.
Role in stack
Primary pick
Primary fit
Local desktop
Trust label
Production-ready
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Good shortlist signal, but the agent should review audit notes, install policy, and outcome evidence before running it.
GitHub adoption
PASS1.3K GitHub stars
Stars/forks activity
INFO1.3K stars, 125 forks; issue activity unavailable in current metadata
Recent maintenance
PASS4d since push
License clarity
PASSMIT
Good signals
Review before install
Recommended action
Use as the primary candidate after human or sandbox review.
Quality profile
Solid option that is likely worth shortlisting for production workflows.
Workflow fit
Operate local tools
I need my agent to operate local files and desktop apps in a repeatable workflow.
Build and ship code
I need a coding agent that can understand a repository, edit code, and review pull requests.
Operate web apps
I need my agent to control a browser, fill forms, and verify web app workflows.
Workflow fit
Inspect, patch, and verify code
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Alternative shortlist
Similar skills that may fit this task.
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Run autonomous deep research over web and local sources
--- name: "omh-adversarial-consensus" description: "[omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then distill into a bundle a separate planner consumes. Use when the user says: adversarial-consensus, adversarial planning, adversarial plan review, red team this plan, red-team this plan, red team the proposal, multi-perspective review, multiple perspectives." metadata: hermes: tags: [workflow, oh-my-hermes, planning] category: planning phase: adversarial-consensus role: planner quality_tier: reviewed-plan-gated ---
# Adversarial Consensus
This is a Hermes-native `adversarial-consensus` workflow skill.
## Why This Exists
`adversarial-consensus` exists because agreement reached by perspectives that read each other is not review — it is convergence. Independent findings, an attack round nobody is allowed to defend against, and a distillation that may only subtract produce objections a single planning pass never surfaces, and the mandatory handoff keeps that bundle from being mistaken for the plan.
## Do Not Use When
- The user wants the plan itself, with options, acceptance criteria, and verification commands; use `ralplan`, which this workflow feeds. - The request is still too ambiguous to state the proposal being attacked; use `deep-interview` first. - The user wants completed code reviewed for defects rather than a proposal attacked before it is built; use `code-review`. - The user wants hostile runtime scenarios against a built change; use `ultraqa`. - One perspective would do: a small local change with no contested decision does not earn three rounds.
## Examples
Good example:
- Prompt: $adversarial-consensus we plan to move session state into Redis before the launch — attack it from every angle before I write the plan. - Expected behavior: Name the roster and their distinct angles, take blind findings from each, run one attack-only round, resolve each objection to defend/refine/concede, distill only into the four buckets, and hand the bundle to `ralplan` as planning input. - Why: The decision is contested and pre-plan, which is exactly where independent objections are worth more than one planner's confidence.
Bad example:
- Prompt: $adversarial-consensus give me the migration plan with the steps and the rollout order. - Expected behavior: Produce the distilled bundle and hand it to `ralplan`; the steps and rollout order are the planner's output, not this workflow's. - Why: The bundle is INPUT to planning. Emitting a plan here skips the reviewed-plan gate and turns the buckets into a task list.
## Completion Checklist
- The roster is named with 3-5 distinct angles, and no two seats argue the same one. - Round-one findings were produced blind, and any perspective that could not be kept blind is named as a broken-independence caveat instead of being presented as independent. - Every cross-attack objection targets another perspective's finding, and no perspective defended itself in that round. - Every objection carries exactly one verdict — defended, refined, or conceded — and conceded findings are struck, not softened. - The bundle contains only Hard Constraints, Decisions, Risks, Open Questions, every line traces to a surviving finding, and nothing new was added at distillation. - The closing message states that the bundle is input, names the follow-on planning workflow, and claims no plan, acceptance, implementation, or verification evidence.
## Recovery Notes
- If the proposal under review cannot be stated in one paragraph, route back to `deep-interview` before opening round one. - If independence was broken — a perspective saw another's findings, or the same seat produced two angles — say so, re-run that perspective on a restated problem, and mark the round's independence as caveated rather than silently continuing. - If a round produces no objections at all, treat that as a roster defect rather than consensus: state which angle is missing and add or replace a seat before distilling. - If distillation would need a fifth bucket, the extra content is a plan trying to escape; move it to the planner handoff instead of widening the bucket set.
## Workflow Lane
- Current lane: **Intent -> plan** (`oh-my-hermes`, `meta-router`, `deep-interview`, `context`, `plan`, `ralplan`, `adversarial-consensus`, `codebase-onboarding`, `+7 more`) - clarify, plan, ship, or loop goals. - If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow. - Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.
## Use When
Use when a proposal, plan, or direction needs independent perspectives to attack it before a plan is written, and the distilled result is meant as input to planning rather than as the plan.
Strong routing signals: `adversarial-consensus`, `$adversarial-consensus`, `adversarial planning`, `adversarial plan review`, `red team this plan`, `red-team this plan`, `red team the proposal`, `multi-perspective review`, `multiple perspectives`, `independent perspectives`, `attack this proposal`, `poke holes in this`, `hyperplan`, `敵対的レビュー`, `多角的レビュー`, `レッドチームレビュー`, `この計画に反論`, `穴を探して`, `적대적 검토`, `다관점 검토`, `여러 관점에서 검토`, `레드팀 검토`, `이 계획 반박`, `허점 찾아`, `对抗式评审`, `多视角评审`, `红队评审`, `反驳这个方案`, `找出漏洞`
## Catalog Metadata
Category: `planning` Phase: `adversarial-consensus` Hermes role: `planner` Quality tier: `reviewed-plan-gated` Reasoning demand: `standard`
Quality bar:
- Name the roster before round one: 3-5 perspectives, each with a stated angle that no other seat covers. The suggested roster is skeptic, validator, researcher, architect, creative; substitute a domain seat when the problem needs one, but two seats arguing the same angle is a duplicate, not a perspective. - Run the rounds in order — independent findings; cross-attack; defend, refine, or concede — and state which round is active in every message, because the independence rule and the no-self-defense rule only mean anything relative to the current round. Load `references/consensus-protocol.md` for the per-round procedure, the per-seat angle table, and the failure modes that make a run look adversarial while producing agreement. - Round one is blind: each perspective produces findings without seeing any other perspective's output, and each finding names its evidence or labels itself an assumption. - Round two attacks only: every perspective attacks other perspectives' findings and never defends or restates its own. A perspective with no objection to any other seat says so explicitly rather than filling the round with agreement. - Round three answers each objection with exactly one verdict — defend with evidence, refine the finding, or concede it — and a conceded finding is struck from the record instead of being softened. - The lead distills only. Nothing new enters at distillation: every line in the bundle traces to a surviving finding, and it goes into one of Hard Constraints, Decisions, Risks, Open Questions — never into a fifth bucket, a recommendation, a sequence of steps, or a task list. - End with the mandatory handoff: state that the bundle is INPUT to planning, name the follow-on planning workflow (`ralplan` for a reviewed plan, `plan` when the shape is already agreed), and stop. Treating the bundle as the plan is the anti-pattern this workflow exists to prevent. - Keep round transitions and perspective outputs as declarations: a stated round change is not evidence that the round happened, and a distilled bundle is not plan acceptance, implementation, review, CI, or merge evidence.
Handoff policy:
Keep every round in Hermes as prepared prompt contracts. The distilled bundle is planning input: hand it to `ralplan` or `plan` for the plan itself, and prepare a selected executor/runtime handoff only after that separate planning pass produces an accepted plan.
Required inputs:
- the proposal, plan draft, or direction under review - the decision the review must inform - known constraints and non-negotiables - the perspective roster and why each angle is distinct
Expected outputs:
- per-perspective independent findings - cross-attack objections attributed to their author - defend, refine, or concede verdict per objection - distilled bundle in the fixed buckets Hard Constraints, Decisions, Risks, Open Questions - mandatory planner handoff naming the follow-on planning workflow
Artifact expectations:
- record the distilled bundle with `omh hermes plan --record`, which writes `<repo>/.omh/plans/<slug>.md` inside a repository and the user-scope OMH store outside one, so the planner pass consumes a file rather than scrollback
Safety rules:
- Do not write the plan here. This workflow produces the input a planner consumes, never the plan itself. - Do not let a perspective read another perspective's findings before its own are recorded; a perspective that saw the others is not an independent objection. - Do not let a perspective defend its own findings during the cross-attack round; that round attacks other perspectives only. - Do not add, rename, or drop a distillation bucket; the closed set is Hard Constraints, Decisions, Risks, Open Questions. - Do not invent evidence on behalf of a perspective; an unsupported objection is recorded as an Open Question, not as a Hard Constraint. - Do not report a round transition, a perspective's output, or the distilled bundle as executed, reviewed, or accepted work; every phase output is a declaration until the user or a wrapper observes it.
## Runtime Evidence
Preferred harness for this skill: `planning`.
```sh omh runtime record --skill adversarial-consensus --harness planning --status started ```
Record observed delegation results; otherwise return `not_available` or `not_observed`. Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence. - Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes. Preserve workflow intent and stop conditions; verify before claiming completion.
Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.
Shared product, compatibility, topology, memory, harness, and execution rules: `omh-routing/references/skill-common-rail.md`. Load it when applicable; otherwise name an unavailable capability.
Source provenance
Decision snapshot
1,309 GitHub stars
Audit
Install and adoption review
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
No agent outcome data yet. The first agent run can report success, setup needs, risk blocks, failure, or not-relevant through /api/agent/outcome.
Install
Free and open source. Review the report before installing into production agents.
Growth loop
Scenario-led draft for omh-adversarial-consensus, ready for a manual X post.
omh-adversarial-consensus: [omh] Hermes Adversarial Consensus workflow: independent perspectives attack a proposal, then... 1.3K stars https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x
Listing + install path for omh-adversarial-consensus: https://www.openagentskill.com/skills/rlaope-omh-adversarial-consensus?ref=x Install: npx skills add rlaope/oh-my-hermes --skill omh-adversarial-consensus
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Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
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Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Review then install
mono-color
Generate original one-ink or controlled two-ink editorial images from any theme, sentence, article idea, object, or reference photo. Always use this skill when the user asks for 单色海报、双色印刷、单色调视觉、蓝色/绿色孔版印刷、risograph、网点照片、复古或当代编辑排版、zine poster, monochrome editorial poster, duotone print, or asks to use the mono-color style. It uses an adaptive white, gray, or pale-beige substrate, no more than two printing inks, active negative space, terse human language, and strong serif/grotesk/mono typography without making retro styling the default or copying a source composition, wording, logo, or artwork. Produce both the final generation prompt and the generated raster image unless the user explicitly asks for prompt only.
1.9K StarsLast30days Skill
Research the last 30 days across Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, then synthesize a grounded brief for an AI agent.
61.0K StarsAcademic Research Skills
Academic Research Skills for Claude Code: research → write → review → revise → finalize
38.4K StarsGPT Researcher
Run autonomous deep research over web and local sources
28.0K StarsPermission surface
filesystem or document access, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness
Permission surface
filesystem or document access, database access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Install readiness