Borrowing it
Nothing to install: this file belongs to Smart-AI-Memory/attune-ai. 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/Smart-AI-Memory/attune-ai/main/.agents/skills/deep-review/SKILL.mdgit clone --depth 1 https://github.com/Smart-AI-Memory/attune-aiWrote 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/smart-ai-memory/attune-ai/deep-review)<a href="https://agentmods.dev/skills/smart-ai-memory/attune-ai/deep-review"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/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/smart-ai-memory/attune-ai/deep-review"><img src="https://agentmods.dev/badge/skills/smart-ai-memory/attune-ai/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 | $0.00016 | $0.00269 |
| Opus 5.5 | $0.00006 | $0.00108 |
| Sonnet 5.5 | $0.00003 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
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 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.
What it actually says
deep-review
Multi-pass code review that runs security, quality, and test gap analysis on a target. Uses subagents to keep context clean.
Context (pre-computed)
git diff --name-only main...HEAD 2>/dev/null || git diff --name-only HEAD~3 2>/dev/null
Instructions
Use AskUserQuestion to scope:
- Which path or files to review?
- Focus: security, quality, test gaps, or all three?
Then run three passes using the Task tool with subagents:
Pass 1: Security
uv run attune workflow run security-audit --path <target>
Pass 2: Quality
uv run attune workflow run code-review --path <target>
Pass 3: Test Gaps
Analyze which functions in the target lack test coverage by cross-referencing source files with test files.
Output
Consolidate findings into a single summary table:
| File | Issue | Severity | Category |
|---|
Group by severity (high → medium → low). End with actionable recommendations.
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 · 52 lines · 16 tokens per session scan A fec09cb33c82
deep-review is a skill published in the GitHub repository Smart-AI-Memory/attune-ai (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 16 tokens to every session and 269 once invoked, about $0.0001 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 2026-08-31.
Other skills, from other repositories
attest
Verifying spec compliance: extracts ACs from specs, adversarially checks conformance, generates BDD scenarios and traceability matrices. Use when impl must be proven to match a PRD/SRS/AC.
guardian
Gatekeeping Git/PR by classifying change essence and recommending granularity, naming, and strategy; the ship recipe also executes PR delivery (create, CI watch, merge, cleanup) with Ask First on merge. Use when PR preparation, commit strategy, or gated PR delivery is needed.
atlas
Analyzing dependencies, circular references, and God Classes; authoring ADRs/RFCs. Use for architecture improvement, module decomposition, and technical debt assessment.
judge
Reviewing code via multi-engine orchestration (Claude + Codex) on three axes — secure, correct, and lean — shipping only findings worth fixing. Use for PR review or pre-commit. Complements Zen.
quill
Adding JSDoc/TSDoc, updating READMEs, replacing any types with proper definitions, and adding high-value comments to complex logic. Use for documentation gaps or type safety.
zen
Refactoring code: variable naming, function extraction, magic number constants, dead code removal. Does not change behavior. Not for bugs (Judge), security (Sentinel), tests (Radar), or features (Builder).