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 agentmods add skills/ai-driven-dev/framework/audit-remediatenpx skills add ai-driven-dev/framework --skill audit-remediategit clone --depth 1 https://github.com/ai-driven-dev/frameworkWhat 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 | $0.00110 | $0.01068 |
| Opus 5 | $0.00055 | $0.00534 |
| Sonnet 5 | $0.00022 | $0.00214 |
| Haiku 4.5 | $0.00011 | $0.00107 |
Grade A, and why
audit-remediate scanned grade A with 0 findings 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 2d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Audit-Remediate
Executes the audit → apply-layer-skill → gate → rollback loop for a single target layer. Each step delegates entirely to the relevant action or layer skill. The macro never inlines layer-specific rules — it routes to the authoritative layer skill for all judgements about what is correct or incorrect.
Available actions
| # | Action | Role | Input |
|---|---|---|---|
| 01 | capture-golden-baseline |
Record the current passing state as the immutable reference point | target layer path + layer skill name |
| 02 | audit-layer |
Enumerate all violations in the target layer per the layer skill | layer skill + target layer files |
| 03 | apply-layer-skill |
Apply the layer skill to fix each violation; log fix-or-clean per file | violation list from 02 + layer skill |
| 04 | gate-golden-and-tests |
Verify golden baseline is byte-identical and all tests pass | baseline from 01 + test suite |
| 05 | verify-or-rollback |
Commit if gate passes; roll back to baseline if gate fails | gate result from 04 |
Default flow
01 → 02 → 03 → 04 → 05
Skip 03 when 02 finds zero violations (clean verdict) — document the skip explicitly: "03 skipped — layer audited clean by <layer-skill>".
Layer skill routing
Apply the correct layer skill in action 03 based on the target directory:
| Target directory | Authoritative layer skill |
|---|---|
domain/formats/ |
format |
domain/capabilities/ |
capability |
domain/tools/ai/ |
tool |
domain/models/ |
domain-model |
application/use-cases/ |
use-case |
infrastructure/adapters/ |
adapter |
application/commands/ |
command |
What ships with it
8 files 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.
- actions/01-capture-golden-baseline.md 1.2 KB
- actions/02-audit-layer.md 2.0 KB
- actions/03-apply-layer-skill.md 1.9 KB
- actions/04-gate-golden-and-tests.md 1.4 KB
- actions/05-verify-or-rollback.md 1.8 KB
- evals/scenarios.json 951 B
- references/gate-criteria.md 2.1 KB
- references/rollback-protocol.md 1.6 KB
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.
- 2d ago First seen · 84 lines · 110 tokens per session scan A b7c97b70bb80
audit-remediate is a skill published in the GitHub repository ai-driven-dev/framework (445 stars, last pushed 2d ago), licensed MIT. It adds 110 tokens to every session and 1,068 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
smoke-test
End-to-end smoke test skill for DeerFlow. Guides through: 1) Pulling latest code, 2) Docker OR Local installation and deployment (user preference, default to Local if Docker network issues), 3) Service availability verification, 4) Health check, 5) Final test report. Use when the user says "run smoke test", "smoke…
image-generation
Use this skill when the user requests to generate, create, imagine, or visualize images including characters, scenes, products, or any visual content. Supports structured prompts and reference images for guided generation.
podcast-generation
Use this skill when the user requests to generate, create, or produce podcasts from text content. Converts written content into a two-host conversational podcast audio format with natural dialogue.
vercel-deploy
Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
zeroclaw
Help users operate and interact with their ZeroClaw agent instance — through both the CLI (zeroclaw commands) and the REST/WebSocket gateway API. Use this skill whenever the user wants to: send messages to ZeroClaw, manage memory or cron jobs, check system status, configure channels or providers, hit the gateway API…
github-issue-triage
Issue triage and lifecycle management agent for ZeroClaw. Use this skill whenever the user wants to: triage open issues, close stale/duplicate/fixed issues, apply labels, run a backlog sweep, enforce the current issue stale policy, or handle a specific issue. Trigger on: 'triage issues', 'issue triage', 'sweep…