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 Benknightdark/neo-skills --skill neo-code-reviewgit clone --depth 1 https://github.com/Benknightdark/neo-skillsWrote 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/benknightdark/neo-skills/neo-code-review)<a href="https://agentmods.dev/skills/benknightdark/neo-skills/neo-code-review"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/neo-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/benknightdark/neo-skills/neo-code-review"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/neo-code-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 | $0.00087 | $0.01228 |
| Opus 5.5 | $0.00035 | $0.00491 |
| Sonnet 5.5 | $0.00017 | $0.00246 |
| Haiku 4.5 | $0.00009 | $0.00123 |
Grade A, and why
neo-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 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Follow this read-only workflow. Report only actionable findings supported by evidence.
Trigger On
- The user requests a code, PR, diff, commit, security, performance, test, or maintainability review.
- The user asks whether code or logic is duplicated across files, or whether hard-coded values should be centralized.
- An AI Agent finishes modifying code, tests, configuration, or scripts before handoff.
Workflow
-
Define the review scope
- Use the files or snippets supplied by the user as the primary scope.
- If the user provides no scope and the current directory is a Git repository, run:
uv run skills/neo-code-review/scripts/git-diff-reviewer.py --working-tree - Use
--stagedfor staged-only changes and--commit <range>for a commit range. - Read surrounding code, related tests, and existing contracts. If no reviewable input exists, report it and stop.
- For a working-tree review, include the helper's tracked diff and each non-ignored untracked file as separate inputs.
-
Load the review rules
- Read review-checklist.md before evaluating code.
- Identify the actual language, framework, and affected behavior from the change. Do not infer unverified rules from filenames.
-
Run the cross-file consistency scan
- Build the comparison set from the review targets and relevant repository source and configuration files. Use
rg --filesand the repository's ignore rules. Exclude dependency, vendor, cache, generated, minified, build, and coverage output unless a file is explicitly in scope. - Inventory changed or reviewed functions, classes, validation and authorization rules, state transitions, request or query construction, error handling, and distinctive literals such as URLs, routes, timeouts, retry counts, thresholds, regexes, feature flags, and error messages.
- Search the comparison set for exact and near-exact matches, then read each match in context. Ignore name and formatting differences when the behavior matches. Treat renamed or slightly rearranged copies as duplicates when their business rules, inputs, side effects, and failure behavior are materially the same.
- Report only meaningful duplication: copied implementation, duplicated business or validation logic, divergent security or state logic, or repeated non-trivial hard-coded configuration. Do not report a match based only on a common keyword, normal one-time literal, test fixture, snapshot, generated file, or vendor code.
- For every cross-file finding, cite both file paths and line numbers. Explain the concrete maintenance, divergence, security, or behavior risk and recommend a specific shared helper, constant, configuration source, or other single source of truth.
- If the user supplied only a snippet or specific files without repository context, state in
## Validationthat cross-file verification was unavailable. Never invent repository matches or line evidence.
- Build the comparison set from the review targets and relevant repository source and configuration files. Use
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 85 lines · 87 tokens per session scan A a3cb04ca20e5
neo-code-review is a skill published in the GitHub repository Benknightdark/neo-skills (7 stars, last pushed 2d ago), licensed MIT. It adds 87 tokens to every session and 1,228 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 2026-08-31.
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