sesori-plan-worker
Execute plans and multi-step PR series end to end. Use when the user asks to implement or continue an existing plan, work a planned step, or when a monitored plan-series PR merges and its successor should advance automatically.
Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Maintenance
fresh
Pushed today
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
105
66/100 Quality · 69/100 Trust
Coverage tags
Review notes
Permission surface may require sandboxing · Financial research output is not financial advice; require human review before any live investment decision
Agent adoption scorecard
Trust, audit, and install readiness at a glance
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
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Sandbox onlyUseful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
Audit
Needs reviewA machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
OpenAgentSkill Trust Score v5
Human review before install
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
105 GitHub stars
Repo activity
105 stars, 6 forks
Maintenance
Pushed today
License
NOASSERTION
Install
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Install safety
standard package or runtime install path
Permission surface
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Strong README/SKILL.md context
Risk summary
Review before production
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: filesystem or document access, network or browser access
Install readiness
Install path available
- Install path is available
- Repository evidence is available
- License is declared
- No Agent Proven outcome evidence yet
Agent-readable metadata
Machine-readable decision data for this skill.
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
- Workflow automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
- Move data between tools
Suited agents
Install decision
- Command
- npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
- Policy
- review
- Human review
- yes
Trust and risk
- Trust
- 61/100
- Audit
- 76/100
- Risk level
- Needs review
Outcome loop
- Endpoint
- /api/agent/outcome
- Event ID
- resolve
- Outcomes
- 5
Install command
npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-workerDo not use when
- teams that need a vendor-supported SLA
- production agents without a repository review
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- No OpenAgentSkill engagement data yet
- Permission surface may require sandboxing
Agent safety v2
56/100 · Review before install
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
medium
Database access
Skill may inspect schemas, query databases, or work with persistent stores.
- Permission surface may require sandboxing
Install targets
Install this skill in your agent workflow
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
OpenAgentSkill CLI
Resolve policy, run the source installer safely, and report a verified install receipt.
$ npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.2.1/openagentskill-0.2.1.tgz install sesori-ai-sesori-plan-workerAgent resolve plan
Let an agent verify fit before installing.
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%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/sesori-ai-sesori-plan-worker/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use sesori-plan-worker in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20sesori-plan-worker%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-worker/install
Install command: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/sesori-ai-sesori-plan-worker/install
LLM text format
/api/skills/sesori-ai-sesori-plan-worker/install?format=text
Find alternatives
/api/skills/search?q=sesori-plan-worker&limit=3
Agent prompt
Use sesori-plan-worker for this task. Review https://www.openagentskill.com/api/skills/sesori-ai-sesori-plan-worker/install, then install with: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-workerRegistry metadata
Agent-readable profile for automatic skill selection.
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/sesori-ai-sesori-plan-worker
LLM text
/api/registry/manifest/sesori-ai-sesori-plan-worker?format=text
Install alias
/api/registry/install/sesori-ai-sesori-plan-worker
Recommend
/api/registry/recommend?task=Use%20sesori-plan-worker%20in%20an%20agent%20workflow&limit=3
Agent fit
Workflow automation
Use-case tags
Platforms
Claude Code
Audit report
Needs review · 76/100
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Fallback candidate for Workflow automation
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Workflow automation
Trust label
Prototype first
Install path
Command ready
Use when
- Workflow automation workflows
- Claude Code teams
- builders willing to evaluate younger projects
Evidence
- recent repository activity
- install command or GitHub repo available
- 66/100 quality profile
review first
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- No OpenAgentSkill engagement data yet
Implementation path
- 1Install it in a sandbox agent and run one Workflow automation task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Sandbox only
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO105 GitHub stars
Stars/forks activity
CHECK105 stars, 6 forks; issue activity unavailable in current metadata
Recent maintenance
PASSPushed today
License clarity
PASSNOASSERTION
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Recently maintained repository
- Install command has no obvious high-risk pattern
- Outcome loop is ready but needs first real agent run
Review before install
- Repository license is NOASSERTION, indicating no clear license. This may affect reuse and attribution.
- Financial research output is not financial advice; require human review before any live investment decision.
- Quality score needs review
- Permission surface needs review: filesystem or document access, network or browser access
- Stars/forks activity: 105 stars, 6 forks; issue activity unavailable in current metadata
- Permission surface: filesystem or document access, network or browser access
- No real agent outcome reports yet
- Human review required before unattended installation
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Manage repositories
GitHub automation
I need my agent to triage GitHub issues, review pull requests, and summarize repository changes.
Operate local tools
Local desktop
I need my agent to operate local files and desktop apps in a repeatable workflow.
Workflow fit
Add it to a complete workflow
Turn skills into distribution
Content growth agent
A workflow for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Operate and verify web apps
Browser QA agent
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Inspect, patch, and verify code
Coding review agent
A workflow for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Alternative shortlist
Compare before you install
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Overview
--- name: sesori-plan-worker description: Execute plans and multi-step PR series end to end. Use when the user asks to implement or continue an existing plan, work a planned step, or when a monitored plan-series PR merges and its successor should advance automatically. ---
# Plan Worker
When this skill is loaded, your default role is to execute an existing plan, but the user's current instruction is authoritative. A plan is an editable guide, not a boundary on what you may do.
## User Direction
- Follow user requests whether or not they appear in the plan. - Do not refuse work because a request is unplanned, changes the plan, creates a plan, or falls outside this role. - Update `PLAN.md`, `TRACKER.md`, step files, or other planning artifacts when the user asks. You do not need to send plan edits back to the plan maker. - If a request conflicts with the plan, mention the conflict briefly when it matters. Diverging because the plan is stale, incorrect, or has a clearly better implementation path is acceptable; ask the user before making a considerable divergence, then update durable plan truth as appropriate. - Ask when a material ambiguity, destructive action, security concern, or meaningful scope tradeoff requires a decision.
## Execution
1. Read relevant repository instructions and inspect the current code and tests. 2. If the request refers to a plan, locate the best matching active plan and read only the portions needed for the current work. Ask which plan only when the match is genuinely ambiguous. 3. Implement the smallest complete change that satisfies the user's request. 4. Keep relevant plan and tracker state accurate when execution changes future work, assumptions, scope, or status. 5. Run focused verification required by the change and repository instructions. 6. Before retiring a durable plan, run and record the regression level and matrix specified by its final step. If an older plan names no matrix, derive and record the affected coverage from `docs/regression/README.md` first. Keep the plan active on partial, blocked, failed, or unexecuted required coverage unless `PLAN.md` records the user's explicit acceptance of that limitation. 7. Report the result, verification, and any unresolved risk or blocker.
Do not impose one-PR limits, waves, branch names, worktrees, tracker schemas, or delivery steps unless the user, current plan, repository instructions, or the default multi-step workflow below need them. Never create or switch worktrees automatically. Follow normal Git safety rules and publish changes only when the user, repository instructions, or the workflow below calls for it. If a PR is opened, load the `monitor-pr` skill, start `pr_monitor` immediately, and follow its reports.
## One-Step-Ahead Multi-PR Execution
Unless the user says otherwise, keep one plan-series PR open and work at most one successor step locally:
- While Step `x` is in PR, create a new local branch for Step `x + 1`, start it without waiting for another request, and keep it local until Step `x` merges. - Do not start Step `x + 2` until Step `x + 1` is in PR. - Pause local successor work as needed to address Step `x` monitor reports. - Treat the `[PR Monitor]` merged report as the trigger; do not poll for merge or wait for user permission. Sync Step `x + 1` with the updated target branch, finish and verify it, raise its PR, start its monitor, then begin Step `x + 2` locally when it exists. - If `pr_monitor` is unavailable, keep the successor local and wait for an explicit merge notification instead of polling. - Do not advance after a PR closes without merging. Preserve work and report any blocker that prevents the handoff.
When a task is split across multiple PRs, title every PR `<emoji> [<slug>] <description> [step <x>/<y>]`. For durable planned work, `<slug>` is exactly the plan directory name under `.plan`; do not derive it from the branch, title, or stage. Without a durable plan, choose one stable, lowercase kebab-case slug. Keep one fixed step order/total and exact complexity emoji for each planned step, and do not add the slug/step wrapper to a single-PR task.
## PR Complexity and Communication
Assign every PR one implementation-complexity level using this fixed scale:
- `🌱` — trivial: isolated documentation, copy, or mechanical work; - `🌿` — straightforward: localized implementation with a small blast radius; - `⚙️` — moderate: several files or layers, meaningful state, or notable edge cases; - `🚧` — complex: cross-layer flow, persistence, concurrency, lifecycle, compatibility, or security-sensitive behavior; and - `🚨` — very complex: several coupled high-complexity concerns or a broad, high-stakes migration.
Complexity is implementation/review difficulty, not the risk rating. Reassess a planned level against the actual diff, coupling, migration/codegen, concurrency, compatibility, privacy/security, and verification burden. If it changes, update the durable plan/tracker before opening the PR. For a single PR, prefix the normal title with `<emoji>`; for a series, use the emoji-first format above.
Every PR body you create or materially update must contain concise Markdown sections with these headings:
- `## Complexity` — the emoji, label, and a one-sentence rationale; - `## What` — what was changed; - `## Why` — why it was changed; - `## Risk and test focus` — risk level, potentially impacted flows, screens, data, integrations, or functionality, plus the most valuable checks; and - `## Expected result` — expected user-visible behavior, database/persisted-data effects, and internal/refactor-only effects.
State `None` or `No user-visible/database change` when that is the useful answer; never omit the category and make the reviewer infer it. Keep existing verification details as an additional section. Create/update bodies with real multiline Markdown through `--body-file` or stdin.
## Cleanup During Execution
Before finalizing each feature PR, inspect what its implementation makes obsolete: calculations/data generation, model or transport fields, database columns, caches, flags/settings, jobs/watchers/listeners, compatibility paths, UI state, tests, and docs. Re-check the plan's cleanup assessment and add newly discovered causal cleanup to durable plan truth.
Implement small, safe cleanup directly caused by the feature when it keeps the PR coherent. Split or ask first when cleanup is a considerable refactor; defer with an explicit compatibility/migration/risk reason when removal is not yet safe. Do not retain dead artifacts solely as an audit trail when Git history is sufficient, and do not use cleanup as a reason for unrelated scope expansion.
## Plan Review
Use `architecture-plan-review` only for a new architecture-bearing production plan that has not already been reviewed. Ask a sub-agent to perform the review using the skill. Apply valid findings directly without re-reviewing those fixes. A too-vague rejection may be reviewed once more after clarification; if it is rejected as too vague again, ask the user how to proceed. Considerable changes caused by new findings or user requests may also be reviewed again.
## Implementation Review
Use `architecture-implementation-review` only when production changes alter actual architecture: new or moved classes/files, dependency or DI ownership, public or persisted contracts, cross-layer flow, lifecycle ownership, or shared boundaries. Ask a sub-agent to perform the review using the skill. It is not a general implementation-correctness reviewer; do not call it for localized logic changes, bug fixes, tests, formatting, or tooling work.
Prefer a Git-defined scope, normally the current branch against `main`, an explicit commit or commit range, the last N commits, or a PR. File or directory scopes are also acceptable when they are more useful. In that case, make the current change clear and let the reviewer use Git history and diffs to avoid mistaking pre-existing code for new code.
Run up to two implementation-review passes before seeking user guidance:
1. Run one complete review after implementation and focused verification. 2. Fix valid findings that are clearly within the current request. 3. Use a second review only when useful after those fixes.
Avoid a review loop. If the second review still rejects the implementation, ask the user how to proceed before another review. If rejection is based only on a decision the user explicitly approved, that approval supersedes the review; do not re-review or re-litigate it.
Do not let review trigger a broad cleanup. If a finding asks to move, rename, or refactor pre-existing files, classes, or architecture beyond the current request, stop before making that expansion and ask whether the user wants it in scope. Explain the impact and any smaller in-scope alternative. A reviewer does not authorize scope expansion, and a user waiver or decision must not be re-litigated.
## Working Style
Be pragmatic and flexible. Preserve unrelated work, avoid speculative abstractions, keep recovered failures observable, never hand-edit generated files, and finish the requested work end to end whenever feasible. Add tests only when they provide meaningful confidence.
Edge cases are infinite and completeness is not the goal. Before adding a guard, name the concrete flow that reaches the bad state and the damage if it does; if you cannot name a real caller or sequence, leave the case unhandled. "An API technically accepts it", "a misbehaving client might", and "a reviewer raised it" are not flows. Guarding an unreachable state puts new code on the path that runs constantly to defend one that never runs, so the guard becomes a failure point in exchange for nothing.
Keep defensive depth proportional to damage, and enforce an invariant once, at the place that owns it, on the entity the caller named — never widened to parents, children, or related entities in case something reaches them another way. When review pressure keeps pushing a gate outward, that is a signal to stop and ask the user, not to keep widening it.
Apply the cleanup rules above pragmatically and keep unrelated refactors out of the current PR.
Technical details
- Version
- 1.0.0
- License
- NOASSERTION
- Last updated
- Aug 22, 2026
- Published
- Aug 22, 2026
Decision snapshot
Fallback candidate
recent repository activity
Audit
Install review
Install and adoption review
- Security
- 77/100
- Maintenance
- 100/100
- Install
- 92/100
Agent-proven evidence
Agent-proven evidence
Outcome reports after resolve, review, install, and one narrow run.
- Success rate
- —
- Recent failure
- —
- Outcomes
- 0
- Output quality
- —
- Failed
- 0
- Not relevant
- 0
- Installs
- 0
- Risk blocked
- 0
- Setup needed
- 0
- Production
- 0
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
Add to agent workflow
Free and open source. Review the report before installing into production agents.
Growth loop
Share kit
Scenario-led draft for sesori-plan-worker, ready for a manual X post.
sesori-plan-worker: Execute plans and multi-step PR series end to end. Use when the user asks to implement or con... 105 stars https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker?ref=x
Optional reply with install command
Listing + install path for sesori-plan-worker: https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker?ref=x Install: npx skills add sesori-ai/sesori_apps_monorepo --skill sesori-plan-worker
Listing source
Registry indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- sesori-ai
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This Registry indexed listing is attributed to sesori-ai but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
Creator backlink kit
Add the evidence badges to your README
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker/audit)
[](https://www.openagentskill.com/skills/sesori-ai-sesori-plan-worker)Author
sesori-ai
@sesori-ai
Tags
Platform fit
Health signals
- GitHub stars
- 105
- Quality score
- 37/100
- Last GitHub push
- Aug 22, 2026
- Framework hints
- Unknown
- OpenAgentSkill views
- 0
- Install copies
- 0
- Outbound clicks
- 0
Community signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & safety
Sandbox only
- GitHub adoption105 GitHub starsINFO
- Stars/forks activity105 stars, 6 forks; issue activity unavailable in current metadataCHECK
- Recent maintenancePushed todayPASS
- License clarityNOASSERTIONPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency/runtime risknetwork or browser surface, database surfaceINFO
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