This file is the runbook for the four poller demos, docker/, docker-memory/, archil/, and openshell/. The five webhook-started providers (cloudflare-containers/, cloudflare-worker/, daytona/, modal/, vercel/) share one agent and one environment, declared in webhook-demo/ and created with ant apply --yes . from that directory. Never run ant apply from this directory: it walks into the poller demos and creates their resources too, and the claude-lock.json it leaves here is then found first by every directory below. Each provider's README is its…
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Long-running Node server (Hono). Sentry posts a signed issue / created webhook → src/app.ts verifies it and hands the issue to src/fixer.ts → one Managed Agents session per issue, with the repository mounted as a github_repository resource, the Sentry MCP credential attached through a vault, a dollar budget, the kickoff message in initial_events, and metadata.sentry_short_id as the dedupe key → the agent reads the issue and Seer's analysis through the Sentry MCP server, reproduces, fixes, pushes autofix/<short-id> → it calls…
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Scheduled deployment: cron → Managed Agents session → Sentry MCP search and optional Seer RCA → /mnt/session/outputs/TRIAGE_REPORT.md. Sentry auth is a refreshable mcp_oauth vault credential; the sandbox never holds a token. Provisioning is ./agents/setup.sh (ant 2.0 or later, jq, uv): it records the slugs in ignored sentry-config.json, runs ant apply --yes agents environments vaults, which creates the agent, environment, and vault and records their IDs in claude-lock.json, then runs oauth_setup.py when the vault has no credential for https://mcp.sentry.dev/mcp. Re-runs publish…
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Things that aren't obvious from the docs and tend to cost debugging time. Use the checklist at the bottom when walking someone through the quickstart. Claude Code owns the plugin's credential and does not expose it; the vault owns the scheduled agent's credential and Anthropic refreshes it. Never inspect or copy Claude Code's credential files, and never put a Sentry token in .env, the shell environment, or the agent prompt. An mcp_oauth credential is keyed by mcp_server_url. When a session's…
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Stateless webhook bridge: Slack app_mention → Managed Agents session (with routing metadata) → session.status_idled webhook → chat.postMessage in-thread. Pull exact shapes from the /claude-api skill's shared/managed-agents-*.md docs. Run the server with bun run dev. Agent provisioning is ant apply --yes agents environments from this directory (ant 2.0 or later; name the directories rather than ., and pass --yes because you have no terminal for its confirmation prompt, or --dry-run to show the plan first): it creates the agent and environment…
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Things that aren't obvious from the docs and tend to cost debugging time. Neither carries the agent's output. Both are signals with IDs. Anthropic's session.status_idled payload is deliberately thin: {type, id}. You follow up with sessions.retrieve(id) (metadata) and sessions.events.list(id) (output). Push the signal, pull the data. On kickoff, set metadata: {slack_channel, slack_thread_ts, slack_team}. When the idle webhook arrives later with only a session ID, retrieve the session, read those keys back, and chat.postMessage to exactly the right thread, with nothing…
A GitHub Action that lets Claude respond to @claude mentions on issues/PRs (tag mode) or run tasks via prompt input (agent mode). Mode is auto-detected: if prompt is provided, it's agent mode; if triggered by a comment/issue event with @claude, it's tag mode. See src/modes/detector.ts. Single entrypoint: src/entrypoints/run.ts orchestrates everything — prepare (auth, permissions, trigger check, branch/comment creation), install Claude Code CLI, execute Claude via base-action/ functions (imported directly, not subprocess), then cleanup (update tracking comment, write step summary). SSH…
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User-specific configuration for this plugin lives at a version-independent path that survives plugin updates: ~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md Rules for every skill, command, and agent in this plugin: 1. READ configuration from that path. Not from this file. 2. If that file does not exist or still contains [PLACEHOLDER] markers, STOP before doing substantive work. Say: "This plugin needs setup before it can give you useful output. Run /ai-governance-legal:cold-start-interview — it takes about 10-15 minutes and every command in this plugin depends on…
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Run an AI impact assessment — structured intake, risk analysis, regulatory classification per regime in scope, policy consistency diff, and recommendation with conditions. Uses the house-style structure learned from the seed impact assessment in `~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md`. Use when user says "impact assessment for", "assess this AI use case", "run an AIA", "generate an AIA", "we need to document this AI system", "AI risk assessment for X", or follows a conditional triage result.
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EU AI Act per-system inventory — track each AI system's role (provider, deployer, importer, distributor, authorized representative, product manufacturer) and risk tier (prohibited, high-risk, limited, minimal, GPAI, GPAI+systemic). Role and tier are assessed per system, not per company. Use when the user says "ai inventory", "add an ai system", "what systems do we have", "classify this ai system", "eu ai act register", or "ai system registry".
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Run the cold-start interview — learns your AI governance practice and writes `~/.claude/plugins/config/claude-for-legal/ai-governance-legal/CLAUDE.md` from your AI policy, a reference impact assessment, and key vendor AI agreements. Use when the practice profile is missing or contains `[PLACEHOLDER]` markers, or when user says "set up ai governance plugin", "onboard me", "configure ai governance".
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Guided customization of your AI governance practice profile — change one thing without re-running the whole cold-start interview. Adjust risk posture, escalation contacts, use-case registry entries, vendor AI positions, AI policy commitments, impact-assessment house style, or matter workspace paths. Use when the user says "change my [thing]", "update my profile", "edit my config", "tune my playbook", or "customize".
Manage matter workspaces — new, list, switch, close, or detach (practice-level). File-management logic for keeping one client or engagement's context separate from every other. Use when working across multiple clients or matters, when the user says "new matter", "switch matter", "list matters", "close matter", or when any substantive skill needs to know which matter it's working in.
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Keep the AI policy current with practice — weekly sweep of saved AIAs, triage results, and vendor reviews to find policy drift, or direct query for a proposed new AI practice. Use when user says "policy sweep", "does our AI policy cover this", "we want to start doing X — does the policy need updating", "run the policy monitor", or on a recurring schedule.
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Draft a firm AI usage policy from published model policies, adapted to your practice profile — a research-and-synthesis tool whose output is a draft for attorney review and adoption, not a finished policy. Use when user says "draft an AI policy", "we need an AI policy", "build an AI usage policy", "our firm needs a GenAI policy", or similar requests to generate a first-cut internal AI policy.
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Diff a new AI regulation or guidance against your current governance posture — surfaces gaps, priorities, and a remediation plan with owners and deadlines. Use when an AI regulation moves (or you learn about one you missed), or when user says "new reg just dropped", "does [regulation] affect us", "gap analysis for EU AI Act", "compliance check against [AI law or guidance]", or pastes regulatory text.
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Classify a proposed AI use case against your registry — approved, conditional, or not approved — and produce required conditions and next steps. Flags cross-plugin handoffs to privacy or product counsel. Use when user says "triage this use case", "can we use AI for X", "is this approved", "what do we need to do to use AI for X".
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Review vendor AI terms — agreement, addendum, or ToS AI provisions — against your governance positions; flag training-on-data, liability, model changes, and AI policy consistency. Use when user says "review this AI agreement", "check OpenAI terms", "what did we agree to with [vendor]", "vendor sent an AI addendum", "is this AI contract okay", or attaches vendor AI terms.
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Plain text files in a repository that tell a coding agent how the project works: commands to run, conventions to follow and things to avoid. CLAUDE.md, AGENTS.md, cursor rules and skills are the common kinds.
CLAUDE.md or AGENTS.md?
CLAUDE.md is read by Claude Code. AGENTS.md is an open format that Codex, Cursor and other agents read. Many projects keep one and point the other at it.
What is a skill?
A folder with a SKILL.md that describes one capability, such as filling PDFs or reviewing code. The agent loads it only when the task calls for it.
Can I search my own team's files too?
Your agents already can, over MCP, limited to the files you're allowed to read. Searching them from this page is coming.
AnthropicReads credentialsCLAUDE.md