Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jhlee0409/all-for-claudecode --skill autogit clone --depth 1 https://github.com/jhlee0409/all-for-claudecodeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jhlee0409/all-for-claudecode/auto)<a href="https://agentmods.dev/skills/jhlee0409/all-for-claudecode/auto"><img src="https://agentmods.dev/badge/skills/jhlee0409/all-for-claudecode/auto/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jhlee0409/all-for-claudecode/auto"><img src="https://agentmods.dev/badge/skills/jhlee0409/all-for-claudecode/auto.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00017 | $0.06484 |
| Opus 5 | $0.00009 | $0.03242 |
| Sonnet 5 | $0.00003 | $0.01297 |
| Haiku 4.5 | $0.00002 | $0.00648 |
Grade B, and why
afc:auto scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
!`cat .claude/afc.config.md 2>/dev/null || echo "[CONFIG NOT FOUND] .claude/afc.config.md not found. Create it with /afc:init."` How it starts
The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/afc:auto — Full Auto Pipeline
Runs clarify? → spec → plan → implement → review → clean fully automatically from a single feature description. Tasks are generated automatically at implement start (no separate tasks phase). Critic Loop runs at each phase (unified safety cap: 5). Convergence terminates early when quality is sufficient. Pre-implementation gates (clarify, TDD pre-gen, blast-radius) run conditionally. Skill Advisor: 5 checkpoints (A–E) at phase boundaries; max 5 auxiliary invocations per pipeline. See
skills/auto/skill-advisor.mdfor details.
Arguments
$ARGUMENTS— (required) Feature description in natural language
Project Config (auto-loaded)
!cat .claude/afc.config.md 2>/dev/null || echo "[CONFIG NOT FOUND] .claude/afc.config.md not found. Create it with /afc:init."
Config Load
Always read .claude/afc.config.md first. Values referenced as {config.*}:
{config.ci}— full CI command{config.gate}— phase gate command{config.test}— test command{config.architecture}— architecture rules{config.code_style}— code style rules
If config missing: ask user to run /afc:init. If declined → abort.
Critic Loop Rules
Always read
${CLAUDE_SKILL_DIR}/../../docs/critic-loop-rules.mdbefore running any Critic pass. Core: minimum 1 concern per criterion + mandatory Adversarial failure scenario each pass + quantitative evidence required. "PASS" as a single word is prohibited. On ESCALATE: pause and present options via AskUserQuestion even in auto mode.
Execution Steps
Phase 0: Preparation
- If
$ARGUMENTSis empty → print "Please enter a feature description." and abort - Check current branch →
BRANCH_NAME. Determine feature name (2-3 keywords, kebab-case). - Preflight Check:
Exit 1 → abort. Warnings (exit 0) → print and continue."${CLAUDE_SKILL_DIR}/../../scripts/afc-preflight-check.sh" - Activate Pipeline Flag:
Creates"${CLAUDE_SKILL_DIR}/../../scripts/afc-pipeline-manage.sh" start {feature}afc/pre-autosafety snapshot, activates Stop Gate Hook, starts change tracking. - Create
.claude/afc/specs/{feature}/→ record asPIPELINE_ARTIFACT_DIR - Initialize Skill Advisor:
ADVISOR_COUNT = 0,ADVISOR_TRANSFORM_USED = falseafc_state_write "advisorCount" "0" afc_state_write "advisorTransformUsed" "false" - Start notification:
Auto pipeline started: {feature} ├─ Clarify? → 1/5 Spec → 2/5 Plan → 3/5 Implement → 4/5 Review → 5/5 Clean └─ Running fully automatically (tasks auto-generated, pre-implementation gates conditional)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 475 lines · 17 tokens per session scan B 9209686fc78f
afc:auto is a skill published in the GitHub repository jhlee0409/all-for-claudecode (7 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 6,484 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
eval-agents
Audit Claude Code agents defined in .claude/agents/ for description specificity, model tier appropriateness, tools scoping, and system prompt quality. Detects dispatch ambiguity between agents, flags over-permissive tool grants, and checks for human-in-the-loop patterns that break programmatic orchestration. Use when…
land-and-deploy
Merge PR, wait for CI, verify deploy, run canary. The complete landing pipeline.
self-assessment
Interactive skill assessment with personalized learning path generation.
orchestrator-lanes
A file-based project-management playbook for a specific Claude Code development orchestrator. It organizes work into lanes, plans, dependency steps, validation phases, and shipping stages.
git-ai-archaeology
Analyze AI config evolution in a git repo. Use when mapping AI adoption history, finding when configs were first introduced, charting commit velocity by month, or identifying maturity phases in a project's AI tooling.
investigate
Systematic root-cause debugging: find the cause before writing any fix.