agentleFS
luigi-dvluigi-dv/react-ts-vite/.claude/skills/deployment-insights/SKILL.md

deployment-insights

Skill1 starsChanged 27 days agoMITView on GitHub

Produce or configure Claude deployment insights — a Markdown report with summary, release notes, risk assessment, bundle notes and a post-deploy checklist generated from commits, diff and build output. Use when asked for release notes, a deployment summary, a risk review before shipping, or to enable/configure "Claude on deployment".

  • Reads credentials

The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 0 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Follow PROMPT.md in this folder exactly: six short sections, every statement grounded in the context, "not enough information" instead of …

    line 31
  2. Very specific:

    If you prefer Claude to inspect the repository in CI, use anthropics/claude-code-action@v1 with prompt: "/deployment-insights", …

    line 46

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Deployment insights

Produce a report

npm run build                                   # optional: adds bundle sizes to the context
npm run deploy:insights -- --dry-run            # see the prompt and context, no API call
npm run deploy:insights                         # writes deployment-insights.md
npm run deploy:insights -- --since v0.1.0 --mode api --model claude-sonnet-5-5

scripts/lib/insights.mjs collects the context (commits and diff since the previous tag, dist/ sizes with gzip, package metadata, architecture, CI/deployment metadata from GITHUB_*/RTV_DEPLOY_URL), uses PROMPT.md in this folder as the system prompt and calls Claude in one of two modes:

  • api — @anthropic-ai/sdk with ANTHROPIC_API_KEY; defaults to claude-opus-5-5, output_config.effort from rtv.config.json, server-side refusal fallbacks enabled. Best for CI.
  • cli — the Claude Code CLI (claude -p) with read-only tools, so Claude can also inspect the repository while writing. Best locally.

--mode auto picks api when a key and the SDK are present, otherwise the CLI.

When you are the agent writing the report yourself

  1. npm run deploy:insights -- --context-only > /tmp/context.md (or run the same git commands).
  2. Follow PROMPT.md in this folder exactly: six short sections, every statement grounded in the context, "not enough information" instead of guesses.
  3. Save it as deployment-insights.md and, for a release, paste it into the GitHub release notes.

Enable "Claude on deployment"

npm run setup -- --claude-insights (or answer yes in the wizard). It copies templates/project/claude-deploy-insights.yml to .github/workflows/, adds @anthropic-ai/sdk as a dev dependency and records the choice in rtv.config.json. Then add the repository secret ANTHROPIC_API_KEY. The workflow runs on published releases, successful deployment_status events (Vercel, Netlify, Render…) and manual dispatch; without the secret it skips itself.

Configuration (rtv.config.json → claude): model (any current Claude id), effort (low…max), deploymentInsights (toggle). Costs: one call per deployment, roughly the size of the diff (capped at 60k characters) plus ~1–2k output tokens.

Customise the prompt

Edit PROMPT.md next to this file. Keep the section structure (teams rely on it), keep the grounding rules, and add project-specific concerns (e.g. "flag any change under src/payments/ as High risk"). Run --dry-run to preview.

Alternative: Claude Code GitHub Action

If you prefer Claude to inspect the repository in CI, use anthropics/claude-code-action@v1 with prompt: "/deployment-insights", anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}, claude_args: "--max-turns 8 --allowedTools Read,Glob,Grep,Bash(git log *),Bash(git diff *)" and display_report: true (requires id-token: write or a github_token). See docs/deployment-insights.md.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.