Loads and manages company context for all C-suite advisor skills. Reads ~/.claude/company-context.md, detects stale context (>90 days), enriches context during conversations, and enforces privacy/anonymization rules before external API calls. Use when starting any C-suite advisor session, when context looks stale or missing, or before sending company data to an external service.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
The memory layer for C-suite advisors. Every advisor skill loads this first. Context is what turns generic advice into specific insight.
company context, context loading, context engine, company profile, advisor context, stale context, context refresh, privacy, anonymization
Step 1 — Check for context file: ~/.claude/company-context.md
Step 2 — Check staleness: Read Last updated field.
[STALE — last updated DATE] noted internally.Step 3 — Parse into working memory. Always active:
| Condition | Confidence | Action |
|---|---|---|
| < 30 days, full interview | High | Use directly |
| 30–90 days, update done | Medium | Use, flag what may have changed |
| > 90 days | Low | Flag stale, prompt refresh |
| Key fields missing | Low | Ask in-session |
| No file | None | Prompt /cs:setup |
If Low: "My context is [stale/incomplete] — I'm assuming [X]. Correct me if I'm wrong."
During conversations, you'll learn things not in the file. Capture them.
Triggers: New number or timeline revealed, key person mentioned, priority shift, constraint surfaces.
Protocol:
[CONTEXT UPDATE: {what was learned}]Never silently overwrite. Always confirm before modifying the context file.
Apply references/anonymization-protocol.md:
Handle gracefully — never block the conversation.
Required:
- Last updated (date)
- Company Identity → What we do
- Stage & Scale → Stage
- Founder Profile → Founder archetype
- Current Challenges → Priority #1
- Goals & Ambition → 12-month target
High-value optional:
- Unfair advantage
- Kill-shot risk
- Avoided decision
- Watch list
Missing required fields: note gaps, work around in session, ask in-session only when critical.
references/anonymization-protocol.md — detailed rules for stripping sensitive data before external callsまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Accessibility audit skill for scanning, fixing, and verifying WCAG 2.2 Level A and AA compliance across React, Next.js, Vue, Angular, Svelte, and plain HTML codebases. Use when auditing accessibility, fixing a11y violations, checking color contrast, generating compliance reports, or integrating accessibility checks into CI/CD pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.
日本語の概要は準備中です。原文の説明を表示しています。
When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.
日本語の概要は準備中です。原文の説明を表示しています。
Answer Engine Optimization (AEO) skill — optimize content to be cited by AI language models (ChatGPT, Perplexity, Claude, Gemini, Mistral) as authoritative sources. Distinct from SEO — AEO optimizes for citation in LLM-generated responses, not search rankings. Use when planning content for AI-first search audiences, auditing existing content for E-E-A-T signals, tracking which pages get cited by which LLMs, or building a citation-friendly content strategy. Triggers — 'AEO audit', 'optimize for ChatGPT', 'get cited by Perplexity', 'LLM citation strategy', 'answer engine optimization', 'content for AI search', 'E-E-A-T audit'. Output is a markdown audit report (default) or JSON for pipeline integration. Stdlib-only Python tools.
日本語の概要は準備中です。原文の説明を表示しています。
Mint a tamper-evident, post-quantum-signed receipt for a consequential agent action (deploy, delete, pay, grant-access, model decision) so it can be verified later from the certificate alone. Use when an autonomous agent takes a side-effecting action that may need to be proven later, or when satisfying EU AI Act Article 12 record-keeping. Three decisions: whether an action needs a receipt, minting it, verifying it. Signing is delegated to the open-source OpenAgentOntology package. Not after-the-fact log analysis; not a hosted notary; not a legal opinion.
日本語の概要は準備中です。原文の説明を表示しています。