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 agentmods add skills/yuri-semenenko/ai-engineering-workspace/pull-request-workflownpx skills add yuri-semenenko/ai-engineering-workspace --skill pull-request-workflowgit clone --depth 1 https://github.com/yuri-semenenko/ai-engineering-workspaceWrote 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/yuri-semenenko/ai-engineering-workspace/pull-request-workflow)<a href="https://agentmods.dev/skills/yuri-semenenko/ai-engineering-workspace/pull-request-workflow"><img src="https://agentmods.dev/badge/skills/yuri-semenenko/ai-engineering-workspace/pull-request-workflow.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 | $0.00038 | $0.00754 |
| Opus 5 | $0.00019 | $0.00377 |
| Sonnet 5 | $0.00008 | $0.00151 |
| Haiku 4.5 | $0.00004 | $0.00075 |
Grade A, and why
pull-request-workflow 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 3d 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pull Request Workflow
Support two related jobs: reviewing PRs and drafting PR descriptions. Use English for GitHub markdown unless the user explicitly asks otherwise.
PR Review
Lead with findings. Classify every meaningful comment:
- Critical — correctness, security, reliability, data loss, auth bypass, broken happy path, severe regression.
- Important — maintainability, scalability, readability, missing tests for non-trivial logic, misleading boundaries.
- Optional — style or preference only when ignoring it has a real cost. Drop pure nitpicks.
Rules:
- Verify PR scope with
gh pr view, PR URL/number, orgit diff <base>...HEAD. - Read the tests and PR description first to recover intended behavior, then read the implementation against that intent.
- Read enough surrounding code to validate each finding.
- Cite
path:linefor every issue. - Order by severity, not by file.
- Classification is severity, not certainty: when unsure a finding is real, phrase it as a question, not an assertion, and do not inflate a Critical you cannot fully trace.
- Delegate the reading, keep the ruling. Run the same sequence every review, not only on large diffs: a cheaper-tier subagent orients on the changed surface, subagents gather by angle (correctness, tests, security when the surface is sensitive, performance) returning compact findings with
path:line, and classification plus the verdict stay on the main model. A subagent finding is evidence, not a ruling. - End with verdict: approve, request changes, or needs discussion.
Format:
## Summary
<scope and verdict>
## Critical
- `path/to/file.ts:42` — <issue> — <impact> — <suggested fix>
## Important
_None._
## Optional
_None._
## Verdict
<approve | request changes | needs discussion> — <one sentence>
Review Loop
For non-trivial PRs or when the user asks for a deeper pass, run the review as a loop:
- Establish scope from the PR, issue, branch name, template, and diff.
- Inspect from independent angles: correctness/regression risk, tests/validation, maintainability, and security/performance only when the diff touches those surfaces.
- Merge findings into one ordered review. Do not duplicate comments across angles.
- Split feedback into fixes worth doing now, optional improvements, and items to defer or ignore with a short reason.
- If the user asks for
autofix, apply only fixes worth doing now, then rerun targeted verification and inspect the final diff.
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.
- 3d ago First seen · 73 lines · 38 tokens per session scan A b650439ad014
pull-request-workflow is a skill published in the GitHub repository yuri-semenenko/ai-engineering-workspace (1 stars, last pushed 5d ago), licensed MIT. It adds 38 tokens to every session and 754 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 2026-08-31.
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