Creator · agentii-ai
Last updated · Sep 3, 2026
Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors
Creator · agentii-ai
Last updated · Sep 3, 2026
Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors
Creator · agentii-ai
Last updated · Sep 3, 2026
Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors
Creator · agentii-ai
Last updated · Sep 3, 2026
Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors
Sandbox only
Install targets
Codex install prompt
Install the "competitive" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/agent-plugins/agentii-equity-agent/skills/agentii/competitive. 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: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors 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":"agentii-ai-competitive","task":"Install competitive","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 agentii-ai/agentii-investment-intelligence --skill competitive
Maintenance
active
3mo since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
203
64/100 Quality · 76/100 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
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
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
203 GitHub stars
Repo activity
203 stars, 16 forks
Maintenance
3mo since push
License
Apache-2.0
Install
npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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 agentii-ai/agentii-investment-intelligence --skill competitiveDo not use when
Alternative
175.1K Stars
npx skills add anthropics/skills --skill frontend-design
Alternative
85.2K Stars
npx skills add Leonxlnx/taste-skill --skill design-taste-frontend
Alternative
1.8K Stars
npx skills add Alisa0808/vox-director --skill vox-director
Alternative
175.1K Stars
npx skills add anthropics/skills --skill canvas-design
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%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agentii-ai-competitive/install
Agent should check
Copy prompt
Task: Use competitive in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agentii-ai-competitive/install
Install command: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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/agentii-ai-competitive/install
LLM text format
/api/skills/agentii-ai-competitive/install?format=text
Find alternatives
/api/skills/search?q=competitive&limit=3
Agent prompt
Use competitive for this task. Review https://www.openagentskill.com/api/skills/agentii-ai-competitive/install, then install with: npx skills add agentii-ai/agentii-investment-intelligence --skill competitiveRegistry 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/agentii-ai-competitive
LLM text
/api/registry/manifest/agentii-ai-competitive?format=text
Install alias
/api/registry/install/agentii-ai-competitive
Recommend
/api/registry/recommend?task=Use%20competitive%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO203 GitHub stars
Stars/forks activity
CHECK203 stars, 16 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Analyze markets
I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Turn one topic into a narrated Vox-style paper-collage explainer or ad video, from script through captions.
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
--- name: competitive multi_ticker_semantics: target_with_required_peers description: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors temporal_scope: default_quarters: 4 max_quarters: 12 description: "Typical lookback: 4 quarters, max: 12" allowed_tools: - search_companies - search_xbrl_facts - search_documents - search_sec_filings - get_company_financials - list_coverage - search_earnings_calendar - get_company_profile - batch_search - read_source_outline - read_source_deep_outline - list_xbrl_concepts - read_source_pages - search_keyword_in_source retrieval_scope: unstructured_document_search min_tool_diversity: 10 ---
<!-- analog: sector-overview -->
## Preflight
Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`.
Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`. ## Triggers
- analyze dim competitive landscape - run dim competitive landscape analysis - produce dim competitive landscape report - dim competitive landscape breakdown - dim competitive landscape deep dive - build a dim competitive landscape - assess dim competitive landscape - quantify dim competitive landscape - compare dim competitive landscape across peers - review dim competitive landscape for - generate dim competitive landscape on - dim competitive landscape for investment decision
## Defaults
| Parameter | Default | Notes | |---|---|---| | lookback_years | 3 | Historical data window | | include_peers | false | Whether to surface a peer comparison block |
<!-- BEGIN port-dimension-prompts methodology + modes -->
## Methodology
### Retrieval Scope
This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
### Retrieval Strategy
Follow the retrieval strategy decision tree in `contracts/retrieval.md`. This skill uses: - Branch (a) for structured financial metrics via `search_xbrl_facts` with `list_xbrl_concepts` pre-condition for unfamiliar concepts. - Branch (c) for single-period document queries via direct `read_source_outline` → `read_source_pages`. - Branch (d) for simple lookups via `get_company_profile` / `search_earnings_calendar`.
**Layer 1 `secondary_label` allowlist **: prefer `?secondary_labels=material_definitive_agreement_1_01,other_events_8_01` to surface M&A / partnership / strategic-action 8-Ks before Layer 2.
### Temporal Scope
Default: 8 fiscal quarters (max 16). Competitive landscape: 8 quarters for market-share trajectories and positioning shifts
### Tool Allowlist
See frontmatter `allowed_tools`.
### Protocol
This skill delivers analyst-grade output via 8 addressable mode(s); invoke with `--mode=<slug>` / `--modes=<slug1>,<slug2>` / `--mode=all` (see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md). The default invocation (no flag) runs the `essentials_modes` subset declared in this skill's frontmatter.
### Analyst Modes
This skill exposes addressable analysis modes (`--mode=<slug>` / `--modes=<s1>,<s2>` / `--mode=all`; see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md)). The full mode definitions and their output templates live in `references/modes.md`. The default invocation runs the essentials subset.
## Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in `references/tool-fallbacks.md`.
## Output File
Write the final deliverable to `{ticker}/{YYYY-MM-DD_HHMM}_competitive_peer-positioning.md` .
## Output Structure
The deliverable is a structured markdown report written to the path in `## Output File`. Full section-by-section template (headings, tables, and field definitions) lives in `references/output-structure.md`. Required elements:
1. **Executive Summary** — headline conclusions (≤200 words). 2. **Core analysis sections** — per this skill's methodology and analyst modes. 3. **Data classification** — tag findings `[FACT]` / `[DEDUCTED]` / `[VIEW]` per `contracts/snapshot-synthesis.md`. 4. **Coverage Gaps & Citations** — inline `/v/` citations are PRIMARY (immediately after each fact); the bottom **Citations** section is a non-duplicative roll-up index. 5. **Output frontmatter** — emit the FR-090 structured block per `contracts/output-frontmatter-schema.md`.
**Citations & memory**: follow `contracts/citation-and-memory.md` — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link; a bottom **Citations** section provides a non-duplicative roll-up index; the closing TUI reply includes a compact **Key Citations** list (headline 5–10 facts) of clickable `/v/` URLs; and append the run to `agentii.md` per `contracts/agentii-md-schema.md`.
## Memory & Snapshot
- **Memory load** (pre-flight): load prior workspace context for the ticker before retrieval — see `contracts/memory-load.md`. - **Structured output frontmatter**: emit the FR-090 block (`key_metrics`, `conclusions`, `facts_count`, `deducted_count`, `views_count`, `citation_count`) per `contracts/output-frontmatter-schema.md`. - **Snapshot synthesis**: after writing the deliverable, update the two-tier snapshot and classify findings as `[FACT]`/`[DEDUCTED]`/`[VIEW]` — see `contracts/snapshot-synthesis.md`. - **Session archival**: record the run under `sessions/{YYYY-MM-DD}/` and update `sessions/INDEX.md` per `contracts/session-format.md`.
## Final Summary (TUI)
End the closing chat reply with a compact **Key Citations** list (headline 5–10 facts), each a clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link, so the user can cmd+click straight to the exact SEC page. See `contracts/citation-and-memory.md`.
## Error Handling
| Failure Mode | Detection | Action | User-Facing Message | |---|---|---|---| | Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." | | Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." | | Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." | | Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." | | MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |
Source provenance
Decision snapshot
recent repository activity
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 competitive, ready for a manual X post.
A practical pick for market research: competitive: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment... 203 stars https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x
Listing + install path for competitive: https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x Install: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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
This Registry indexed listing is attributed to agentii-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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive/audit)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)agentii-ai
@agentii-ai
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
Frontend Design
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175.1K StarsTaste Skill: Anti-Slop Frontend
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175.1K StarsSandbox only
Install targets
Codex install prompt
Install the "competitive" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/agent-plugins/agentii-equity-agent/skills/agentii/competitive. 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: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors 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":"agentii-ai-competitive","task":"Install competitive","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 agentii-ai/agentii-investment-intelligence --skill competitive
Maintenance
active
3mo since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
203
64/100 Quality · 76/100 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
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
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
203 GitHub stars
Repo activity
203 stars, 16 forks
Maintenance
3mo since push
License
Apache-2.0
Install
npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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 agentii-ai/agentii-investment-intelligence --skill competitiveDo not use when
Alternative
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npx skills add Leonxlnx/taste-skill --skill design-taste-frontend
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Alternative
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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%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agentii-ai-competitive/install
Agent should check
Copy prompt
Task: Use competitive in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agentii-ai-competitive/install
Install command: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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/agentii-ai-competitive/install
LLM text format
/api/skills/agentii-ai-competitive/install?format=text
Find alternatives
/api/skills/search?q=competitive&limit=3
Agent prompt
Use competitive for this task. Review https://www.openagentskill.com/api/skills/agentii-ai-competitive/install, then install with: npx skills add agentii-ai/agentii-investment-intelligence --skill competitiveRegistry 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/agentii-ai-competitive
LLM text
/api/registry/manifest/agentii-ai-competitive?format=text
Install alias
/api/registry/install/agentii-ai-competitive
Recommend
/api/registry/recommend?task=Use%20competitive%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO203 GitHub stars
Stars/forks activity
CHECK203 stars, 16 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Analyze markets
I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Turn one topic into a narrated Vox-style paper-collage explainer or ad video, from script through captions.
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
--- name: competitive multi_ticker_semantics: target_with_required_peers description: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors temporal_scope: default_quarters: 4 max_quarters: 12 description: "Typical lookback: 4 quarters, max: 12" allowed_tools: - search_companies - search_xbrl_facts - search_documents - search_sec_filings - get_company_financials - list_coverage - search_earnings_calendar - get_company_profile - batch_search - read_source_outline - read_source_deep_outline - list_xbrl_concepts - read_source_pages - search_keyword_in_source retrieval_scope: unstructured_document_search min_tool_diversity: 10 ---
<!-- analog: sector-overview -->
## Preflight
Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`.
Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`. ## Triggers
- analyze dim competitive landscape - run dim competitive landscape analysis - produce dim competitive landscape report - dim competitive landscape breakdown - dim competitive landscape deep dive - build a dim competitive landscape - assess dim competitive landscape - quantify dim competitive landscape - compare dim competitive landscape across peers - review dim competitive landscape for - generate dim competitive landscape on - dim competitive landscape for investment decision
## Defaults
| Parameter | Default | Notes | |---|---|---| | lookback_years | 3 | Historical data window | | include_peers | false | Whether to surface a peer comparison block |
<!-- BEGIN port-dimension-prompts methodology + modes -->
## Methodology
### Retrieval Scope
This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
### Retrieval Strategy
Follow the retrieval strategy decision tree in `contracts/retrieval.md`. This skill uses: - Branch (a) for structured financial metrics via `search_xbrl_facts` with `list_xbrl_concepts` pre-condition for unfamiliar concepts. - Branch (c) for single-period document queries via direct `read_source_outline` → `read_source_pages`. - Branch (d) for simple lookups via `get_company_profile` / `search_earnings_calendar`.
**Layer 1 `secondary_label` allowlist **: prefer `?secondary_labels=material_definitive_agreement_1_01,other_events_8_01` to surface M&A / partnership / strategic-action 8-Ks before Layer 2.
### Temporal Scope
Default: 8 fiscal quarters (max 16). Competitive landscape: 8 quarters for market-share trajectories and positioning shifts
### Tool Allowlist
See frontmatter `allowed_tools`.
### Protocol
This skill delivers analyst-grade output via 8 addressable mode(s); invoke with `--mode=<slug>` / `--modes=<slug1>,<slug2>` / `--mode=all` (see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md). The default invocation (no flag) runs the `essentials_modes` subset declared in this skill's frontmatter.
### Analyst Modes
This skill exposes addressable analysis modes (`--mode=<slug>` / `--modes=<s1>,<s2>` / `--mode=all`; see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md)). The full mode definitions and their output templates live in `references/modes.md`. The default invocation runs the essentials subset.
## Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in `references/tool-fallbacks.md`.
## Output File
Write the final deliverable to `{ticker}/{YYYY-MM-DD_HHMM}_competitive_peer-positioning.md` .
## Output Structure
The deliverable is a structured markdown report written to the path in `## Output File`. Full section-by-section template (headings, tables, and field definitions) lives in `references/output-structure.md`. Required elements:
1. **Executive Summary** — headline conclusions (≤200 words). 2. **Core analysis sections** — per this skill's methodology and analyst modes. 3. **Data classification** — tag findings `[FACT]` / `[DEDUCTED]` / `[VIEW]` per `contracts/snapshot-synthesis.md`. 4. **Coverage Gaps & Citations** — inline `/v/` citations are PRIMARY (immediately after each fact); the bottom **Citations** section is a non-duplicative roll-up index. 5. **Output frontmatter** — emit the FR-090 structured block per `contracts/output-frontmatter-schema.md`.
**Citations & memory**: follow `contracts/citation-and-memory.md` — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link; a bottom **Citations** section provides a non-duplicative roll-up index; the closing TUI reply includes a compact **Key Citations** list (headline 5–10 facts) of clickable `/v/` URLs; and append the run to `agentii.md` per `contracts/agentii-md-schema.md`.
## Memory & Snapshot
- **Memory load** (pre-flight): load prior workspace context for the ticker before retrieval — see `contracts/memory-load.md`. - **Structured output frontmatter**: emit the FR-090 block (`key_metrics`, `conclusions`, `facts_count`, `deducted_count`, `views_count`, `citation_count`) per `contracts/output-frontmatter-schema.md`. - **Snapshot synthesis**: after writing the deliverable, update the two-tier snapshot and classify findings as `[FACT]`/`[DEDUCTED]`/`[VIEW]` — see `contracts/snapshot-synthesis.md`. - **Session archival**: record the run under `sessions/{YYYY-MM-DD}/` and update `sessions/INDEX.md` per `contracts/session-format.md`.
## Final Summary (TUI)
End the closing chat reply with a compact **Key Citations** list (headline 5–10 facts), each a clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link, so the user can cmd+click straight to the exact SEC page. See `contracts/citation-and-memory.md`.
## Error Handling
| Failure Mode | Detection | Action | User-Facing Message | |---|---|---|---| | Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." | | Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." | | Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." | | Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." | | MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |
Source provenance
Decision snapshot
recent repository activity
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 competitive, ready for a manual X post.
A practical pick for market research: competitive: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment... 203 stars https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x
Listing + install path for competitive: https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x Install: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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
This Registry indexed listing is attributed to agentii-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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive/audit)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)agentii-ai
@agentii-ai
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
Frontend Design
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Install targets
Codex install prompt
Install the "competitive" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/agent-plugins/agentii-equity-agent/skills/agentii/competitive. 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: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors 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":"agentii-ai-competitive","task":"Install competitive","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 agentii-ai/agentii-investment-intelligence --skill competitive
Maintenance
active
3mo since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
203
64/100 Quality · 76/100 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
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
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
203 GitHub stars
Repo activity
203 stars, 16 forks
Maintenance
3mo since push
License
Apache-2.0
Install
npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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 agentii-ai/agentii-investment-intelligence --skill competitiveDo not use when
Alternative
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Alternative
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Alternative
1.8K Stars
npx skills add Alisa0808/vox-director --skill vox-director
Alternative
175.1K Stars
npx skills add anthropics/skills --skill canvas-design
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%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agentii-ai-competitive/install
Agent should check
Copy prompt
Task: Use competitive in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agentii-ai-competitive/install
Install command: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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/agentii-ai-competitive/install
LLM text format
/api/skills/agentii-ai-competitive/install?format=text
Find alternatives
/api/skills/search?q=competitive&limit=3
Agent prompt
Use competitive for this task. Review https://www.openagentskill.com/api/skills/agentii-ai-competitive/install, then install with: npx skills add agentii-ai/agentii-investment-intelligence --skill competitiveRegistry 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/agentii-ai-competitive
LLM text
/api/registry/manifest/agentii-ai-competitive?format=text
Install alias
/api/registry/install/agentii-ai-competitive
Recommend
/api/registry/recommend?task=Use%20competitive%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO203 GitHub stars
Stars/forks activity
CHECK203 stars, 16 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Analyze markets
I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Turn one topic into a narrated Vox-style paper-collage explainer or ad video, from script through captions.
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
--- name: competitive multi_ticker_semantics: target_with_required_peers description: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors temporal_scope: default_quarters: 4 max_quarters: 12 description: "Typical lookback: 4 quarters, max: 12" allowed_tools: - search_companies - search_xbrl_facts - search_documents - search_sec_filings - get_company_financials - list_coverage - search_earnings_calendar - get_company_profile - batch_search - read_source_outline - read_source_deep_outline - list_xbrl_concepts - read_source_pages - search_keyword_in_source retrieval_scope: unstructured_document_search min_tool_diversity: 10 ---
<!-- analog: sector-overview -->
## Preflight
Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`.
Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`. ## Triggers
- analyze dim competitive landscape - run dim competitive landscape analysis - produce dim competitive landscape report - dim competitive landscape breakdown - dim competitive landscape deep dive - build a dim competitive landscape - assess dim competitive landscape - quantify dim competitive landscape - compare dim competitive landscape across peers - review dim competitive landscape for - generate dim competitive landscape on - dim competitive landscape for investment decision
## Defaults
| Parameter | Default | Notes | |---|---|---| | lookback_years | 3 | Historical data window | | include_peers | false | Whether to surface a peer comparison block |
<!-- BEGIN port-dimension-prompts methodology + modes -->
## Methodology
### Retrieval Scope
This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
### Retrieval Strategy
Follow the retrieval strategy decision tree in `contracts/retrieval.md`. This skill uses: - Branch (a) for structured financial metrics via `search_xbrl_facts` with `list_xbrl_concepts` pre-condition for unfamiliar concepts. - Branch (c) for single-period document queries via direct `read_source_outline` → `read_source_pages`. - Branch (d) for simple lookups via `get_company_profile` / `search_earnings_calendar`.
**Layer 1 `secondary_label` allowlist **: prefer `?secondary_labels=material_definitive_agreement_1_01,other_events_8_01` to surface M&A / partnership / strategic-action 8-Ks before Layer 2.
### Temporal Scope
Default: 8 fiscal quarters (max 16). Competitive landscape: 8 quarters for market-share trajectories and positioning shifts
### Tool Allowlist
See frontmatter `allowed_tools`.
### Protocol
This skill delivers analyst-grade output via 8 addressable mode(s); invoke with `--mode=<slug>` / `--modes=<slug1>,<slug2>` / `--mode=all` (see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md). The default invocation (no flag) runs the `essentials_modes` subset declared in this skill's frontmatter.
### Analyst Modes
This skill exposes addressable analysis modes (`--mode=<slug>` / `--modes=<s1>,<s2>` / `--mode=all`; see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md)). The full mode definitions and their output templates live in `references/modes.md`. The default invocation runs the essentials subset.
## Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in `references/tool-fallbacks.md`.
## Output File
Write the final deliverable to `{ticker}/{YYYY-MM-DD_HHMM}_competitive_peer-positioning.md` .
## Output Structure
The deliverable is a structured markdown report written to the path in `## Output File`. Full section-by-section template (headings, tables, and field definitions) lives in `references/output-structure.md`. Required elements:
1. **Executive Summary** — headline conclusions (≤200 words). 2. **Core analysis sections** — per this skill's methodology and analyst modes. 3. **Data classification** — tag findings `[FACT]` / `[DEDUCTED]` / `[VIEW]` per `contracts/snapshot-synthesis.md`. 4. **Coverage Gaps & Citations** — inline `/v/` citations are PRIMARY (immediately after each fact); the bottom **Citations** section is a non-duplicative roll-up index. 5. **Output frontmatter** — emit the FR-090 structured block per `contracts/output-frontmatter-schema.md`.
**Citations & memory**: follow `contracts/citation-and-memory.md` — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link; a bottom **Citations** section provides a non-duplicative roll-up index; the closing TUI reply includes a compact **Key Citations** list (headline 5–10 facts) of clickable `/v/` URLs; and append the run to `agentii.md` per `contracts/agentii-md-schema.md`.
## Memory & Snapshot
- **Memory load** (pre-flight): load prior workspace context for the ticker before retrieval — see `contracts/memory-load.md`. - **Structured output frontmatter**: emit the FR-090 block (`key_metrics`, `conclusions`, `facts_count`, `deducted_count`, `views_count`, `citation_count`) per `contracts/output-frontmatter-schema.md`. - **Snapshot synthesis**: after writing the deliverable, update the two-tier snapshot and classify findings as `[FACT]`/`[DEDUCTED]`/`[VIEW]` — see `contracts/snapshot-synthesis.md`. - **Session archival**: record the run under `sessions/{YYYY-MM-DD}/` and update `sessions/INDEX.md` per `contracts/session-format.md`.
## Final Summary (TUI)
End the closing chat reply with a compact **Key Citations** list (headline 5–10 facts), each a clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link, so the user can cmd+click straight to the exact SEC page. See `contracts/citation-and-memory.md`.
## Error Handling
| Failure Mode | Detection | Action | User-Facing Message | |---|---|---|---| | Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." | | Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." | | Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." | | Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." | | MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |
Source provenance
Decision snapshot
recent repository activity
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 competitive, ready for a manual X post.
A practical pick for market research: competitive: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment... 203 stars https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x
Listing + install path for competitive: https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x Install: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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
This Registry indexed listing is attributed to agentii-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
Show the canonical listing, current trust and audit signals, and real Agent-Proven evidence where developers evaluate the repository.
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[](https://www.openagentskill.com/skills/agentii-ai-competitive/audit)
[](https://www.openagentskill.com/skills/agentii-ai-competitive?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)agentii-ai
@agentii-ai
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Sandbox only
Frontend Design
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
175.1K StarsTaste Skill: Anti-Slop Frontend
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
85.2K StarsVox Director
Turn one topic into a narrated Vox-style paper-collage explainer or ad video, from script through captions.
1.8K StarsCanvas Design
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
175.1K StarsSandbox only
Install targets
Codex install prompt
Install the "competitive" agent skill from https://github.com/agentii-ai/agentii-investment-intelligence/tree/main/plugins/agent-plugins/agentii-equity-agent/skills/agentii/competitive. 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: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors 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":"agentii-ai-competitive","task":"Install competitive","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 agentii-ai/agentii-investment-intelligence --skill competitive
Maintenance
active
3mo since push
Risk
Needs review
Permission surface may require sandboxing
GitHub quality
203
64/100 Quality · 76/100 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
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
Run only in a sandbox and compare close alternatives before using it for real work.
Stars
203 GitHub stars
Repo activity
203 stars, 16 forks
Maintenance
3mo since push
License
Apache-2.0
Install
npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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 agentii-ai/agentii-investment-intelligence --skill competitiveDo not use when
Alternative
175.1K Stars
npx skills add anthropics/skills --skill frontend-design
Alternative
85.2K Stars
npx skills add Leonxlnx/taste-skill --skill design-taste-frontend
Alternative
1.8K Stars
npx skills add Alisa0808/vox-director --skill vox-director
Alternative
175.1K Stars
npx skills add anthropics/skills --skill canvas-design
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%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/agentii-ai-competitive/install
Agent should check
Copy prompt
Task: Use competitive in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20competitive%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/agentii-ai-competitive/install
Install command: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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/agentii-ai-competitive/install
LLM text format
/api/skills/agentii-ai-competitive/install?format=text
Find alternatives
/api/skills/search?q=competitive&limit=3
Agent prompt
Use competitive for this task. Review https://www.openagentskill.com/api/skills/agentii-ai-competitive/install, then install with: npx skills add agentii-ai/agentii-investment-intelligence --skill competitiveRegistry 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/agentii-ai-competitive
LLM text
/api/registry/manifest/agentii-ai-competitive?format=text
Install alias
/api/registry/install/agentii-ai-competitive
Recommend
/api/registry/recommend?task=Use%20competitive%20in%20an%20agent%20workflow&limit=3
Agent fit
Research agents
Use-case tags
Platforms
Claude Code
Audit report
A machine-readable review of install readiness, security metadata, maintenance, and adoption risk.
Agent decision cockpit
Prototype with this skill first; keep a fallback candidate ready.
Role in stack
Fallback candidate
Primary fit
Research agents
Trust label
Prototype first
Install path
Command ready
Use when
Evidence
review first
Implementation path
Trust profile
Useful candidate with missing or mixed trust signals. Keep it in an isolated workspace until the outcome loop proves task fit.
GitHub adoption
INFO203 GitHub stars
Stars/forks activity
CHECK203 stars, 16 forks; issue activity unavailable in current metadata
Recent maintenance
PASS3mo since push
License clarity
PASSApache-2.0
Good signals
Review before install
Recommended action
Run only in a sandbox and compare close alternatives before using it for real work.
Quality profile
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Investigate faster
I need my agent to research a topic, compare sources, and produce a concise report.
Analyze markets
I need my agent to analyze markets, financial data, filings, portfolios, and quant strategies.
Search private knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Workflow fit
Find, compare, and synthesize
A workflow for agents that gather sources, compare claims, summarize long material, and draft useful research briefs.
Ingest, retrieve, and cite
A workflow for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Operate and verify web apps
A workflow for agents that navigate products, fill forms, take screenshots, and verify real user flows across web applications.
Alternative shortlist
Similar skills that may fit this task.
Guidance for distinctive, intentional UI design, typography, visual direction, and non-template-like product interfaces.
Design and implementation guidance for distinctive landing pages, portfolios, product demos, and purposeful redesigns.
Turn one topic into a narrated Vox-style paper-collage explainer or ad video, from script through captions.
Create original visual art, posters, PNG assets, and PDF documents through a clear design philosophy.
--- name: competitive multi_ticker_semantics: target_with_required_peers description: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment, Porter five forces, industry competition, competitive advantage analysis, market positioning, strategic group mapping, compare competitors temporal_scope: default_quarters: 4 max_quarters: 12 description: "Typical lookback: 4 quarters, max: 12" allowed_tools: - search_companies - search_xbrl_facts - search_documents - search_sec_filings - get_company_financials - list_coverage - search_earnings_calendar - get_company_profile - batch_search - read_source_outline - read_source_deep_outline - list_xbrl_concepts - read_source_pages - search_keyword_in_source retrieval_scope: unstructured_document_search min_tool_diversity: 10 ---
<!-- analog: sector-overview -->
## Preflight
Run the canonical pre-flight sequence — MCP health probe, ticker resolution, workspace `style.md` override, memory load, and coverage check. See `contracts/preflight.md`.
Include the `X-Agentii-Trace` header on every tool call per `contracts/x-agentii-trace-header.md`. ## Triggers
- analyze dim competitive landscape - run dim competitive landscape analysis - produce dim competitive landscape report - dim competitive landscape breakdown - dim competitive landscape deep dive - build a dim competitive landscape - assess dim competitive landscape - quantify dim competitive landscape - compare dim competitive landscape across peers - review dim competitive landscape for - generate dim competitive landscape on - dim competitive landscape for investment decision
## Defaults
| Parameter | Default | Notes | |---|---|---| | lookback_years | 3 | Historical data window | | include_peers | false | Whether to surface a peer comparison block |
<!-- BEGIN port-dimension-prompts methodology + modes -->
## Methodology
### Retrieval Scope
This skill performs unstructured document search at scale (10-K, 10-Q, 8-K filings spanning multiple fiscal periods). The three-layer agent-use-ready retrieval protocol (Document Discovery → Page Map → Deep Read) applies to all unstructured document search at scale.
### Retrieval Strategy
Follow the retrieval strategy decision tree in `contracts/retrieval.md`. This skill uses: - Branch (a) for structured financial metrics via `search_xbrl_facts` with `list_xbrl_concepts` pre-condition for unfamiliar concepts. - Branch (c) for single-period document queries via direct `read_source_outline` → `read_source_pages`. - Branch (d) for simple lookups via `get_company_profile` / `search_earnings_calendar`.
**Layer 1 `secondary_label` allowlist **: prefer `?secondary_labels=material_definitive_agreement_1_01,other_events_8_01` to surface M&A / partnership / strategic-action 8-Ks before Layer 2.
### Temporal Scope
Default: 8 fiscal quarters (max 16). Competitive landscape: 8 quarters for market-share trajectories and positioning shifts
### Tool Allowlist
See frontmatter `allowed_tools`.
### Protocol
This skill delivers analyst-grade output via 8 addressable mode(s); invoke with `--mode=<slug>` / `--modes=<slug1>,<slug2>` / `--mode=all` (see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md). The default invocation (no flag) runs the `essentials_modes` subset declared in this skill's frontmatter.
### Analyst Modes
This skill exposes addressable analysis modes (`--mode=<slug>` / `--modes=<s1>,<s2>` / `--mode=all`; see [Mode syntax](../../../../docs/commands/MODE_SYNTAX.md)). The full mode definitions and their output templates live in `references/modes.md`. The default invocation runs the essentials subset.
## Tool Fallbacks
Per-tool failure modes and fallback actions are tabulated in `references/tool-fallbacks.md`.
## Output File
Write the final deliverable to `{ticker}/{YYYY-MM-DD_HHMM}_competitive_peer-positioning.md` .
## Output Structure
The deliverable is a structured markdown report written to the path in `## Output File`. Full section-by-section template (headings, tables, and field definitions) lives in `references/output-structure.md`. Required elements:
1. **Executive Summary** — headline conclusions (≤200 words). 2. **Core analysis sections** — per this skill's methodology and analyst modes. 3. **Data classification** — tag findings `[FACT]` / `[DEDUCTED]` / `[VIEW]` per `contracts/snapshot-synthesis.md`. 4. **Coverage Gaps & Citations** — inline `/v/` citations are PRIMARY (immediately after each fact); the bottom **Citations** section is a non-duplicative roll-up index. 5. **Output frontmatter** — emit the FR-090 structured block per `contracts/output-frontmatter-schema.md`.
**Citations & memory**: follow `contracts/citation-and-memory.md` — ≥1 citation per 200 words; every material fact, table row, and metric is immediately followed by its inline clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link; a bottom **Citations** section provides a non-duplicative roll-up index; the closing TUI reply includes a compact **Key Citations** list (headline 5–10 facts) of clickable `/v/` URLs; and append the run to `agentii.md` per `contracts/agentii-md-schema.md`.
## Memory & Snapshot
- **Memory load** (pre-flight): load prior workspace context for the ticker before retrieval — see `contracts/memory-load.md`. - **Structured output frontmatter**: emit the FR-090 block (`key_metrics`, `conclusions`, `facts_count`, `deducted_count`, `views_count`, `citation_count`) per `contracts/output-frontmatter-schema.md`. - **Snapshot synthesis**: after writing the deliverable, update the two-tier snapshot and classify findings as `[FACT]`/`[DEDUCTED]`/`[VIEW]` — see `contracts/snapshot-synthesis.md`. - **Session archival**: record the run under `sessions/{YYYY-MM-DD}/` and update `sessions/INDEX.md` per `contracts/session-format.md`.
## Final Summary (TUI)
End the closing chat reply with a compact **Key Citations** list (headline 5–10 facts), each a clickable `https://agentii.ai/v/{ticker}/{citation_id}/{N}` link, so the user can cmd+click straight to the exact SEC page. See `contracts/citation-and-memory.md`.
## Error Handling
| Failure Mode | Detection | Action | User-Facing Message | |---|---|---|---| | Missing data | Data API returns empty result set | Widen date range and retry once | "No data available for {ticker} in requested window." | | Partial data | Data API returns <80% expected records | Proceed with coverage gaps section | "Analysis based on partial data; see Coverage Gaps section." | | Sector mismatch | Peer sector != target sector | Filter out mismatched peers | "Removed {n} peer(s) due to sector mismatch." | | Insufficient history | Ticker <3 years on public markets | Downgrade to limited-history profile | "Limited historical data; analysis adjusted accordingly." | | MCP unreachable | Preflight probe fails | Halt with actionable error | "agentii data plane unreachable; check connection." |
Source provenance
Decision snapshot
recent repository activity
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 competitive, ready for a manual X post.
A practical pick for market research: competitive: Competitive landscape analysis, competitor comparison, peer positioning, market share dynamics, competitive moat assessment... 203 stars https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x
Listing + install path for competitive: https://www.openagentskill.com/skills/agentii-ai-competitive?ref=x Install: npx skills add agentii-ai/agentii-investment-intelligence --skill competitive
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Permission surface
filesystem or document access, network or browser access
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Docs
Usable metadata, review docs
Risk summary
Install readiness
Permission surface
filesystem or document access, network or browser access
Agent outcomes
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Docs
Usable metadata, review docs
Risk summary
Install readiness
Permission surface
filesystem or document access, network or browser access
Agent outcomes
No agent outcome data yet
Docs
Usable metadata, review docs
Risk summary
Install readiness