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 Maudeunfledged834/startup-founder-skills --skill code-reviewgit clone --depth 1 https://github.com/Maudeunfledged834/startup-founder-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/maudeunfledged834/startup-founder-skills/code-review)<a href="https://agentmods.dev/skills/maudeunfledged834/startup-founder-skills/code-review"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/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/maudeunfledged834/startup-founder-skills/code-review"><img src="https://agentmods.dev/badge/skills/maudeunfledged834/startup-founder-skills/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 | $0.00045 | $0.01714 |
| Opus 5.5 | $0.00018 | $0.00686 |
| Sonnet 5.5 | $0.00009 | $0.00343 |
| Haiku 4.5 | $0.00005 | $0.00171 |
Grade A, and why
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.
This is a copy
100% identical to code-review — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
When to Use
- The user shares code (file, snippet, or diff) and asks for feedback
- They paste a pull request or want to know if code is production-ready
- Pre-merge quality gate or bug hunting
- Reviewing architectural decisions in a PR
Context Required
From startup-context: tech stack, product stage, team size. Also need from the user:
- The code or diff to review
- What the code is supposed to do (PR purpose or feature context)
- Any specific concerns (performance, security, correctness)
- Language and framework if not obvious from the code
Workflow
Follow a structured five-step methodology. Each step must be completed before moving to the next.
- Context — Understand and summarize the PR's purpose before any analysis. Recap the intent back to the user in 1-2 sentences. If unclear, ask before proceeding. Never start reviewing without understanding what the code is trying to accomplish.
- Structure — Evaluate architectural decisions and design patterns:
- Does the code belong in the right module/layer?
- Are abstractions appropriate (not too many, not too few)?
- Does this change align with the existing codebase patterns?
- For non-obvious design choices, acknowledge the author's reasoning before proposing alternatives.
- Details — Assess code quality across multiple dimensions:
- Correctness: Logic errors, off-by-one bugs, null/undefined handling, race conditions, edge cases
- Security: OWASP Top 10 baseline — injection, broken auth, data exposure, XSS, access control, misconfig, insecure deserialization, vulnerable components
- Performance: N+1 queries, unnecessary re-renders, O(n^2) on large datasets, missing caching, memory leaks
- Naming and clarity: Do names communicate intent? Are functions focused on a single responsibility?
- Tests — Validate test coverage with equal rigor as code review:
- Are behavioral assertions present (not just implementation testing)?
- Are edge cases and error paths covered?
- Are tests brittle or resilient to refactoring?
- What test cases are missing?
- Feedback — Generate a prioritized, categorized report with specific code examples and concrete improvements. Recognize strong patterns and good decisions explicitly.
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 · 151 lines · 45 tokens per session scan A ef4b4cd1d870
code-review is a skill published in the GitHub repository Maudeunfledged834/startup-founder-skills (8 stars, last pushed 16d ago), licensed MIT. It adds 45 tokens to every session and 1,714 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to code-review, differing in 0 lines, and is treated as a copy.
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