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 wrg32786/aigent-os --skill self-reviewgit clone --depth 1 https://github.com/wrg32786/aigent-osWrote 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/wrg32786/aigent-os/self-review)<a href="https://agentmods.dev/skills/wrg32786/aigent-os/self-review"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/self-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/wrg32786/aigent-os/self-review"><img src="https://agentmods.dev/badge/skills/wrg32786/aigent-os/self-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00069 | $0.00895 |
| Opus 5.5 | $0.00028 | $0.00358 |
| Sonnet 5.5 | $0.00014 | $0.00179 |
| Haiku 4.5 | $0.00007 | $0.00089 |
Grade A, and why
Self-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 1mo 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Self-Review
Run an explicit second-pair-of-eyes pass on non-trivial work before declaring done. Quality of review depends on quality of question.
When to RUN self-review
- More than ~30 lines OR multi-file change
- Hot path (many requests flow through this code)
- Subtle interactions with code you might have missed
- Prompt or output affecting user-visible content
- Code not worked in recently (mental model might be stale)
- Any genuine uncertainty after writing the change
When to SKIP self-review
- One-line edit, mechanical fix, obvious diff
- Pure rename or move with no logic change
- Code just written with full context, low blast radius
- Cost-benefit doesn't justify (review takes longer than the fix did)
If skipping, say so explicitly: "Skipping self-review — N-line trivial fix." Don't silently bypass.
How to execute
Step 1 — Set context (3-5 lines max)
State, in plain language:
- The bug / feature / what was asked
- The cause (what was actually wrong)
- The fix (what was actually changed)
Step 2 — List specific changes
- path/to/file_one.ts:L123-L145 — replaced regex with structured parser
- path/to/file_two.ts:L56 — added null guard for empty corpus
- path/to/config.json — bumped diversity_threshold 0.6 → 0.75
Step 3 — Ask 4-6 specific verification questions
Bad asks (do not produce useful answers):
- "Is this good?"
- "Does this look right?"
- "Any issues?"
- "Did I miss anything?"
Good asks (concrete, falsifiable, named):
- "Does the new keyword order ever cause a wrong branch in
routeRequest?" - "Does the diversity rule reach the model in the same prompt as the recent-titles list?"
- "Is the early return at line 47 still bypassing this check?"
- "If
recent_titlesis empty (first run), does the sort comparator return stable output?" - "Does the schema migration handle the existing 12K
nullrows or only new inserts?"
Each question must:
- Reference a specific file:line or function name
- State the failure mode you're worried about
- Be answerable yes/no after a focused read
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.
- 1mo ago First seen · 101 lines · 69 tokens per session scan A 9244e9900ed3
Self-Review is a skill published in the GitHub repository wrg32786/aigent-os (23 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 895 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-01.
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