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 ilang-ai/autocode --skill full-reviewgit clone --depth 1 https://github.com/ilang-ai/autocodeWrote 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/ilang-ai/autocode/full-review)<a href="https://agentmods.dev/skills/ilang-ai/autocode/full-review"><img src="https://agentmods.dev/badge/skills/ilang-ai/autocode/full-review/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/ilang-ai/autocode/full-review"><img src="https://agentmods.dev/badge/skills/ilang-ai/autocode/full-review.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 | $0.00168 |
| Opus 5 | $0.00009 | $0.00084 |
| Sonnet 5 | $0.00003 | $0.00034 |
| Haiku 4.5 | $0.00002 | $0.00017 |
Grade A, and why
full-review 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 10d 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.
What it actually says
::PRIOR{completion:assume_incomplete|authority:developer} ::PRIOR{execution:act_when_safe|authority:developer}
::GENE{full-review|conf:confirmed|scope:global} T:review_every_file T:report_in_user_language T:check_logic_edges_security_hardcoded T:human_readable_commit_messages A:partial_review⇒full_review A:skip_on_save⇒never
::ACTIVATE{full-review} ON:before_save ON:before_deploy ON:session_end
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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.
- 10d ago First seen · 24 lines · 17 tokens per session scan A f32f081c761f
full-review is a skill published in the GitHub repository ilang-ai/autocode (86 stars, last pushed 2mo ago), licensed MIT. It adds 17 tokens to every session and 168 once invoked, about $0.0001 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.
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