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 tommyvo/useful-prompts --skill local-code-reviewgit clone --depth 1 https://github.com/tommyvo/useful-promptsWrote 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/tommyvo/useful-prompts/local-code-review)<a href="https://agentmods.dev/skills/tommyvo/useful-prompts/local-code-review"><img src="https://agentmods.dev/badge/skills/tommyvo/useful-prompts/local-code-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/tommyvo/useful-prompts/local-code-review"><img src="https://agentmods.dev/badge/skills/tommyvo/useful-prompts/local-code-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 | $0.00020 | $0.02285 |
| Opus 5.5 | $0.00008 | $0.00914 |
| Sonnet 5.5 | $0.00004 | $0.00457 |
| Haiku 4.5 | $0.00002 | $0.00229 |
Grade A, and why
local-code-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 24d 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 — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Local Code Review
Goal
Provide a comprehensive report with suggestions for a code change that hasn't been committed yet. The report should list things that the developer should review, any optimizations that can be applied, and any security concerns.
CRITICAL: MANDATORY FIRST STEP
YOU MUST run git diff HEAD as your ABSOLUTE FIRST action before doing ANYTHING else.
- DO NOT attempt to review code from context or memory
- DO NOT skip this step under any circumstances
- DO NOT proceed to the next step without running this command first
- DO NOT assume you know what changed
If you do not run git diff HEAD first, you are failing to follow instructions.
Process
Follow these steps IN ORDER. DO NOT skip any step:
- STEP 1 - Get Changes via Git (MANDATORY): Run
git diff HEADin the terminal to retrieve ALL uncommitted changes. This is your primary source of truth for what to review. You can read existing files in the current directory for additional context if needed. - STEP 2 - Choose Review Mode: Check the size of the diff with
git diff HEAD --shortstat. If it touches more than 15 files or more than 800 changed lines, or the user asked for subagents, use parallel subagents as described in Large Reviews: Parallel Subagents below. Otherwise, or if the user asked not to use subagents, review it yourself in a single pass. - STEP 3 - Generate The Report: Generate the comprehensive report in markdown format. List improvements and rate them in terms of priority using the emoji system.
- STEP 4 - Apply Appropriate Fixes: After generating the report, automatically apply any suggestions that are appropriate. Appropriate fixes are those that: (1) are in scope of the changes being made, and (2) would improve security, readability, fix obvious bugs, or address style/lint issues. Skip suggestions that don't relate to the changes being made or would require significant architectural decisions. IMPORTANT: If you decide to not apply any of the suggested changes, please highlight the ones that were skipped and explain why. Please do not save the report in the filesystem. You should only output to chat.
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.
- 24d ago Changed 7f6a84d3340e
- 1mo ago Changed · +51 lines 7fd7bdfda642
- 2mo ago First seen · 124 lines · 20 tokens per session scan A 73a11ab4cb53
local-code-review is a skill published in the GitHub repository tommyvo/useful-prompts (4 stars, last pushed 2d ago), licensed Unlicense. It adds 20 tokens to every session and 2,285 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.
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