/cs:onboard — Founder interview that populates ~/.claude/company-context.md using the canonical 7-dimension cs-onboard schema. The first command to run when starting with c-level-agents. Use when setting up the virtual C-suite for a new company, or when advisors lack company context — e.g. before a first /cs:boardroom or after a fundraise changes the numbers.
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Command: /cs:onboard
The first command to run when adopting c-level-agents. A structured founder interview that produces ~/.claude/company-context.md — the file every cs-* advisor reads before responding. Without this, the advisors are guessing.
~/.claude/company-context.md — a single file with the durable facts about the company. Read by:
cs-chief-of-staff (routing decisions)/cs:brief (assumptions in any new decision)Canonical schema: ~/.claude/company-context.md is owned by the cs-onboard skill and follows its 7-dimension schema (../../../c-level-advisor/skills/cs-onboard/templates/company-context-template.md): Company Identity, Stage & Scale, Founder Profile, Team & Culture, Market & Competition, Current Challenges, Goals & Ambition. The 12 questions above are a faster structured intake that populates that same file — Identity/Business/Financial → Stage & Scale, Team → Team & Culture, Quarter priorities/risks → Current Challenges + Goals & Ambition. Write [not captured] for dimensions the quick intake doesn't reach (Founder Profile, Market & Competition); run the full cs-onboard interview to fill them. Never create a second context file or a divergent layout.
The intake summary captured by the 12 questions:
# Company Context
**Generated:** YYYY-MM-DD
**Last updated:** YYYY-MM-DD
## Identity
- **Company:** <name>
- **Pitch:** <one sentence>
- **Stage:** <stage>
- **HQ + remote:** <distribution>
## Business
- **Model:** <type>
- **ICP:** <description + named customer>
- **ACV:** $<median> (range $<low> - $<high>)
- **Deal count (LTM):** N
- **ARR growth (YoY):** X%
## Financial
- **Cash on hand:** $<amount>
- **Net burn (monthly):** $<amount>
- **Runway base:** N months
- **Runway bear:** N months
- **Last raise:** $<amount> at $<post> in <month YYYY>, led by <investor>
## Team
- **Total headcount:** N
- **Eng:** N | Product: N | GTM: N | Ops: N | G&A: N
## Quarter
- **Top priorities (Q<X> YYYY):**
1. <priority>
2. <priority>
3. <priority>
- **Top risks:**
1. <risk>
2. <risk>
3. <risk>
## Routing Hints
[Optional: any role the founder wants to use sparingly or rely on heavily]
~/.claude/company-context.mdln -sf ~/company-vault/00-meta/company-context.md ~/.claude/company-context.md
/cs:boardroom for a high-stakes decisionBy default, ~/.claude/company-context.md is local to the founder's machine. To make it persistent across machines / shareable:
../../references/llm-wiki-bridge.md~/.claude/cs-onboard — the underlying interview protocolcontext-engine — reads this file../../references/llm-wiki-bridge.mdVersion: 1.0.0
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。