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/sflandergan/agentic-coding/github-pr-commentsnpx skills add sflandergan/agentic-coding --skill github-pr-commentsgit clone --depth 1 https://github.com/sflandergan/agentic-codingWhat 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 | $0.00024 | $0.00980 |
| Opus 5 | $0.00012 | $0.00490 |
| Sonnet 5 | $0.00005 | $0.00196 |
| Haiku 4.5 | $0.00002 | $0.00098 |
Grade A, and why
github-pr-comments 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 yesterday.
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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub PR Comments
Use this for solo-maintainer PR review workflows where feedback is stored as plain GitHub comments rather than formal review submissions.
Baseline Failure To Avoid
Agents naturally mix comment APIs: they may read reviews when feedback is actually an issue comment, post a top-level reply instead of an inline thread reply, or patch someone else's comment instead of posting a reply.
Skill Scope
This skill owns PR comment mechanics: fetching comments and diffs, distinguishing issue comments from inline review comments, obtaining exact target IDs, and posting approved replies through project scripts.
This skill does not own role-level review orchestration. The calling review agent decides how to interpret comments, validate technical claims, combine them with other findings, suggest fixes, edit files, dispatch implementers, or perform final self-review.
Read Comments
Use the bundled read-only helper before proposing fixes. It fetches top-level issue comments, unresolved inline review threads, and the PR diff:
bash .agents/skills/github-pr-comments/scripts/fetch-pr-comments.sh [<pr>]
When <pr> is omitted, the script auto-detects the PR number from the current branch.
Run the command exactly as shown, without quoting the script path. The review-code agent has explicit auto-permissions for this command form.
The helper prints a compact comment summary first, then full PR metadata, issue comments, inline comments, and the PR diff. Use the summary for grouping and the full JSON sections for exact databaseId values.
Optional read-only modes:
bash .agents/skills/github-pr-comments/scripts/fetch-pr-comments.sh [<pr>] --comments-only
bash .agents/skills/github-pr-comments/scripts/fetch-pr-comments.sh [<pr>] --diff-only
bash .agents/skills/github-pr-comments/scripts/fetch-pr-comments.sh [<pr>] --json
Do not call the GitHub CLI directly for reading PR metadata, issue comments, inline comments, or diffs. The helper is the stable interface for this workflow.
What ships with it
2 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.
- yesterday First seen · 87 lines · 24 tokens per session scan A 3669e0b474ed
github-pr-comments is a skill published in the GitHub repository sflandergan/agentic-coding (2 stars, last pushed 2mo ago), licensed MIT. It adds 24 tokens to every session and 980 once invoked, about $0.0001 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…
imagegen
Generate or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output…
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…