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 ulises-jeremias/agent-toolkit --skill deep-reviewgit clone --depth 1 https://github.com/ulises-jeremias/agent-toolkitWrote 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/ulises-jeremias/agent-toolkit/deep-review)<a href="https://agentmods.dev/skills/ulises-jeremias/agent-toolkit/deep-review"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/deep-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/ulises-jeremias/agent-toolkit/deep-review"><img src="https://agentmods.dev/badge/skills/ulises-jeremias/agent-toolkit/deep-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 | $0.00057 | $0.01728 |
| Opus 5 | $0.00028 | $0.00864 |
| Sonnet 5 | $0.00011 | $0.00346 |
| Haiku 4.5 | $0.00006 | $0.00173 |
Grade A, and why
deep-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 9d 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Review
A strict, evidence-cited code review rubric for when a change needs more than a surface checklist. It pushes the reviewer to be ambitious about structure — not merely to identify local cleanup, but to find "code judo" moves: restructurings that preserve behavior while making the implementation dramatically simpler, smaller, and more direct.
When to use
- The user asks for a "deep review", "deep code quality audit", "thermo-nuclear review", "harsh maintainability review", or "review for abstraction quality".
- A PR touches large files, shared layers, or risk-prone abstractions.
- The
code-revieweragent flags that a change needs structural (not stylistic) feedback.
Review contract
Findings carry severity and confidence, each with an evidence citation (file:line or diff hunk) — no ungrounded opinions:
- Severity:
critical(block merge) ·warning(should fix) ·suggestion(consider). - Confidence:
high(certain from the evidence) ·medium(likely, needs a look) ·low(hypothesis).
Baseline prompt
Perform a deep code quality audit of the current branch's changes. Rethink how to structure / implement the changes to meaningfully improve code quality without impacting behavior. Work to improve abstractions, modularity, reduce spaghetti code, improve succinctness and legibility. Be ambitious — if there is a clear path to improving the implementation that involves restructuring, pursue it. Be extremely thorough and rigorous. Measure twice, cut once.
Non-negotiable standards
-
Be ambitious about structural simplification. Do not stop at "this could be cleaner". Look for opportunities to reframe the change so whole branches, helpers, modes, conditionals, or layers disappear. Prefer the solution that makes the code feel inevitable in hindsight. If there is a path to delete complexity rather than rearrange it, push hard for that path.
-
Do not let a PR push a file over 1000 lines without a very strong reason. Treat this as a strong smell. Prefer extracting helpers, subcomponents, or modules. If the diff crosses the threshold, ask whether the code should be decomposed first.
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.
- 9d ago First seen · 149 lines · 57 tokens per session scan A 60ebf4d7ec8f
deep-review is a skill published in the GitHub repository ulises-jeremias/agent-toolkit (16 stars, last pushed today), licensed MIT. It adds 57 tokens to every session and 1,728 once invoked, about $0.0003 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
audit
Audits recent work against its Definition of Done and project patterns. Runs the test suite, compares code against the spec, and reports PASS / PARTIAL / FAIL. Also runs the Critical Gate — a safety scan of the diff for destructive or dangerous operations. Generates an incremental prompt pack for any gaps found. With…
pr-alignment-loop
Iterate a PR to its final form by running two opposing reviewer droids (reviewer-robustness and reviewer-minimalist) in a bounded back-and-forth loop. The main orchestrator synthesizes their feedback, makes edits, runs tests, and stops when both approve, on stagnation, or after 3 rounds. Use when the user asks to…
review-all
Use when the user asks for a deep review, full review, comprehensive review, production readiness assessment, full audit, multi-domain audit, "security and reliability and code review", or "review everything". Also use when the user explicitly requests performance review alongside the comprehensive request (e.g.…
active-review
Use when the user wants to prepare for a manual PR code review and asks for help targeting it — a terse PR summary, ranked files to read first, and paste-ready inline comment drafts with GitHub deep-links. Triggers: "active review this PR", "walk me through this PR", "help me review this", "give me inline comments to…
review-documentation
Review documentation quality and sync with implementation across Go doc comments, proto comments, OpenAPI specs, markdown files, and example tests. Use when the user asks for a documentation review, doc audit, or wants to check that docs are in sync with code.
review-api-compat
Use when the user asks for an API compatibility review, breaking change review, proto breaking change review, buf breaking review, OpenAPI compatibility check, gRPC backwards compatibility audit, "are these API changes breaking", "did we break the wire", contract evolution review, or backwards-compatibility audit on…