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 jpantsjoha/ai-native-developer-experience --skill pr-reviewergit clone --depth 1 https://github.com/jpantsjoha/ai-native-developer-experienceWrote 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/jpantsjoha/ai-native-developer-experience/pr-reviewer)<a href="https://agentmods.dev/skills/jpantsjoha/ai-native-developer-experience/pr-reviewer"><img src="https://agentmods.dev/badge/skills/jpantsjoha/ai-native-developer-experience/pr-reviewer.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00777 |
| Opus 5 | $0.00021 | $0.00388 |
| Sonnet 5 | $0.00008 | $0.00155 |
| Haiku 4.5 | $0.00004 | $0.00078 |
Grade A, and why
pr-reviewer 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 8d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Reviewer
Receipts, not polish. A review that says "looks good" is not a review. A review that says "line 47 will panic on a nil pointer and here is the fix" is a review.
This skill runs a structured code review and produces a verdict: approve, approve with comments, or request changes. Every finding is actionable. No findings without evidence.
When to use
- Before merging any PR
- When reviewing agent-generated code before committing
- When a significant refactor or new feature is complete
- As part of the
release-readinesschecklist
Procedure
-
Scope the review — fetch the diff. Identify:
- Files changed and their purpose
- The stated intent of the PR (what problem does it solve?)
- Any linked spec, issue, or ADR
-
Correctness pass — look for bugs, not style:
- Null / nil / undefined access on values that could be absent
- Off-by-one errors in loops or index operations
- Error returns that are silently ignored
- Race conditions if the code is concurrent
- Missing input validation at trust boundaries (user input, external API responses)
- Logic that diverges from the stated intent of the PR
-
Reuse pass — look for duplication:
- Does this code reimplement something that already exists in the codebase?
- Is there a stdlib or already-installed dependency that does this?
- Can the new code be expressed using an existing abstraction?
-
Simplification pass — look for unnecessary complexity:
- Can this be fewer lines without losing clarity?
- Is there an abstraction that has only one implementation? (remove it)
- Is there a dependency added for something a few lines of code would do?
- Is there "scaffolding for later" that should not exist yet?
-
Security and data boundary pass — look for:
- Secrets or credentials in code or logs
- User-controlled input reaching a shell, SQL query, or file path without validation
- Data crossing a tenant or trust boundary without an explicit check
- Missing authentication or authorisation checks on new endpoints
What ships with it
1 file 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.
- 8d ago First seen · 76 lines · 42 tokens per session scan A 72cae7cef0a2
pr-reviewer is a skill published in the GitHub repository jpantsjoha/ai-native-developer-experience (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 42 tokens to every session and 777 once invoked, about $0.0002 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
md-audit
Read-only code quality audit — scan the current working directory for common issues (bugs, dead code, security hotspots, missing error handling) and return a prioritised findings report. No files are edited. Use when asked to "audit the code", "quick audit", "find issues", "code scan", or "what's wrong with this…
comet-verify
Comet Phase 4: Verify and Close. Invoke with /comet-verify. Verify implementation matches design, handle development branch.
comet-review
A read-only review guide for checking the current Comet change, a managed software-change workflow. It focuses on correctness, security, and boundary problems without changing files or advancing the workflow.
comet-github-pr-review
A read-only review process for pull requests in Comet's GitHub repositories. A pull request is a proposed code change; the review checks its current code, related issue, comments, merge status, and automated checks.
issue-analyze
GitHub Issue and PR review thread deep analysis with Codex blind verdict. Use when: analyzing issue root cause, classifying problems, investigation planning, triaging PR review comments for actionability. Not for: fixing bugs (use bug-fix), code exploration (use code-explore). Output: classified analysis + verdict…
load-pr-review
Load GitHub PR review comments into AI session — analyze, triage, plan. Default: analysis-only (no auto-fix). Use when: reviewing PR feedback, planning fixes, addressing review comments, replying to reviewers. Not for: creating reviews (use codex-review-fast), creating PRs (use create-pr), viewing PR status (use…