mirror of https://github.com/alirezarezvani/claude-skills.git synced 2026-09-06 08:15:58 +00:00

docs(andreessen): run update-docs sync pipeline + mkdocs nav for v2.8.3

- Bump headline counts: 329 -> 330 skills, ~448 -> ~451 tools, ~586 -> ~590
  references, 49+ -> 50+ agents, 79+ -> 81+ commands across CLAUDE.md, README,
  docs/index.md, docs/getting-started.md, mkdocs.yml.
- README productivity row 5 -> 6; add andreessen entry.
- CLAUDE.md: v2.8.3 highlights section + version/status/date footer.
- marketplace.json metadata + top-level description counts incremented.
- mkdocs.yml nav: add andreessen skill page, cs-andreessen agent,
  /cs:andreessen + /cs:pmf-check commands.
- Regenerate docs pages via generate-docs.py (andreessen skill/agent/commands;
  also reconciles claude-coach pages + dev-drift on code-reviewer/role-skill pages).
- mkdocs build verified clean (only pre-existing unrelated relative-link warnings).

https://claude.ai/code/session_01SF6MzfjHurZMt5JUFET9h3

2026-05-24 01:52:12 +00:00

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title	description
/cs-fullstack-review — Slash Command for AI Coding Agents	Fullstack engineering review — walks the 7 Matt Pocock forcing questions, picks the profile, forks into POWERFUL specialists (api-design-reviewer. Slash command for Claude Code, Codex CLI, Gemini CLI.

/cs-fullstack-review

:material-console: Slash Command :material-github: Source

Use the cs-fullstack-engineer agent (which uses context: fork to keep the parent thread clean) to handle this inquiry:

$ARGUMENTS

Forcing-question library

Canonical source: engineering-team/skills/senior-fullstack/references/forcing_questions.md (7 questions, one-per-turn, recommendation + canon citation per question).

Team size now + 12-month headcount
Deployment cadence (per-PR / daily / weekly / quarterly)
Customer-facing / internal tool / marketing site
One-year p50 + p99 traffic forecast
Hiring-against vs training-into the stack
Year-one monthly cloud + SaaS budget ceiling
Three verifiable success criteria with numeric targets

Routing protocol

Walk the 7 forcing questions in engineering-team/skills/senior-fullstack/references/forcing_questions.md. One per turn. Recommend the answer with cited canon. Track in /tmp/fullstack-grill-<date>.md.
Surface kill criteria — if any question trips one (e.g., "microservices day 1, team size 3"), STOP and resolve before proceeding.

Run the deterministic profile picker:

python engineering-team/skills/senior-fullstack/scripts/fullstack_decision_engine.py \
  --team-size <N> --team-size-12mo <N12> --cadence <c> \
  --user-facing <true|false> --budget <USD/mo> \
  --traffic-p99-rps <N> --data-sensitivity <tier>

Surface the matched profile + runner-up tradeoff (if within 15%).
Fork into specialists (one at a time, depth-first):
- api-design-reviewer for API contract
- database-designer for schema
- slo-architect for reliability target
- ci-cd-pipeline-builder for the pipeline
- performance-profiler for perf baseline
- cs-karpathy-reviewer before any commit

Output expectations (≤ 200-word digest)

Matched profile + reason
Three verifiable success criteria with numeric targets
Named approver chain
List of specialists invoked + artifact paths
Recommended next sub-skill (if any)

Anti-patterns

❌ Bundling forcing questions — one per turn.
❌ Skipping the kill-criteria check.
❌ Reimplementing specialist scope. Fork — don't duplicate.
❌ Auto-approving production changes. Always name the human approver.

Customization

Profiles live at engineering-team/skills/senior-fullstack/profiles/. To customize for your org:

Copy saas-startup.json (or whichever best fits) to <your-org>.json.
Edit constraints, stack_recommendations, success_thresholds, named_approver_chain.
The decision engine auto-discovers new profile JSONs.

/cs:frontend-review — frontend-only deep dive
/cs:backend-review — backend-only deep dive
/cs:engineer-grill — cross-role 21-question forcing-question runner
/karpathy-check — Karpathy 4-principle review before commit

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