Borrowing it
Nothing to install: this file belongs to agno-agi/context. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/agno-agi/context/main/.agents/skills/review-and-improve/SKILL.mdgit clone --depth 1 https://github.com/agno-agi/contextWrote 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/agno-agi/context/review-and-improve)<a href="https://agentmods.dev/skills/agno-agi/context/review-and-improve"><img src="https://agentmods.dev/badge/skills/agno-agi/context/review-and-improve/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/agno-agi/context/review-and-improve"><img src="https://agentmods.dev/badge/skills/agno-agi/context/review-and-improve.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 | $0.00110 | $0.02840 |
| Opus 5 | $0.00055 | $0.01420 |
| Sonnet 5 | $0.00022 | $0.00568 |
| Haiku 4.5 | $0.00011 | $0.00284 |
Grade B, and why
review-and-improve scanned grade B with 2 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
- Live container reachable: `curl -sSf http://localhost:8000/health` returns 200. If not, ask the user to `docker compose up -d --build` first — Step 4 needs a live container. (`docker compose ps` is unreliable from work Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Live container reachable: `curl -sSf http://localhost:8000/health` returns 200. If not, ask the user to `docker compose up -d --build` first — Step 4 needs a live container. (`docker compose ps` is unreliable from work How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review and Improve
Coding-agent workflow — a
/slash-commandyour coding agent (Claude Code, Codex, …) runs while developing this repo. Not a runtime skill the deployed @context agent runs; those live inskills/.
You are sweeping the whole repo for public-consumption readiness — docs accuracy, the context agent reachable end to end, scripts that actually do what the docs claim, no stale env vars, format + validate clean. Most drift is mechanical (renamed file, missing entry in example.env, a provider missing from the architecture diagram) and you fix it in place. The rest is a punch list you surface to the user.
This is a recurring sweep — meant to be re-run regularly. On a clean repo it ends with "no diffs"; on a dirty one it brings everything back to coherent.
AGENTS.md is the source of truth for repo conventions; CLAUDE.md is a symlink to it — edit once, both update.
What you auto-fix vs. what you flag
Auto-fix in place (no asking):
- Stale file paths in any doc.
- Missing entries in
example.envfor env vars the code actually reads. - Stale entries in
example.envfor vars nothing reads — delete unless the surrounding comment block describes them as optional/future ("alternate model providers", "future feature"). Flag instead of fixing if intent is unclear. - Architecture diagram in
AGENTS.mdmissing a wired provider or runtime skill (or listing one that's gone). - An agent file on disk not imported in
app/main.py(rare — single-agent product, but the AGENTS.md recipe allows more; add the import + append toagents=[...]). - Missing
quick_promptsblock for a registered agent (draft three from the agent'sINSTRUCTIONS; flag the new entries so the user can refine). - Missing or wrong cross-links between skill files in
.agents/skills/. - Single-line factual claim in one doc contradicted by another doc or by code (e.g. one doc says "hot-reload picks up new agents" while another says a restart is required) — auto-fix the doc, not the code.
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 · 160 lines · 110 tokens per session scan B 970c0948126d
review-and-improve is a skill published in the GitHub repository agno-agi/context (11 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 110 tokens to every session and 2,840 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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