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 nearform/lastlight --skill pr-commentgit clone --depth 1 https://github.com/nearform/lastlightWrote 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/nearform/lastlight/pr-comment)<a href="https://agentmods.dev/skills/nearform/lastlight/pr-comment"><img src="https://agentmods.dev/badge/skills/nearform/lastlight/pr-comment/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/nearform/lastlight/pr-comment"><img src="https://agentmods.dev/badge/skills/nearform/lastlight/pr-comment.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 | $0.00041 | $0.01147 |
| Opus 5.5 | $0.00016 | $0.00459 |
| Sonnet 5.5 | $0.00008 | $0.00229 |
| Haiku 4.5 | $0.00004 | $0.00115 |
Grade A, and why
pr-comment scanned grade A with 1 finding 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 13d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
GitHub operations via `github_*` MCP tools only — never `gh` CLI, `curl`, or raw HTTP. How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Comment
A maintainer @mentioned the bot on a PR with a question (not a request to write code, and not "review this"). The question is the entire job — answer it with evidence, in one comment. Examples: "does this consider X?", "why did we change Y?", "is the new function thread-safe?", "regression risk for existing callers?".
For general issue questions use issue-comment; for a full review use
pr-review.
Procedure
1. Read the PR and the question
github_get_pull_request→ title, body, base, head.prNumberin the Context block is your target — go straight there. Do not callgithub_list_pull_requeststo "find" or "confirm" it; you were handed it, and listing dumps every open PR for nothing.- The triggering question is in
context.commentBody. Answer that question — don't generalise to a review or answer a different one.
2. Investigate with the diff in hand
Get the diff and read the code needed to answer well — a real answer about thread-safety or regression risk needs the surrounding code, not just the hunk.
- Cap: 8 file reads per invocation.
- "Does it consider X?" → also check whether tests in the diff cover X.
- "Regression risk?" → find callers of any function whose signature/behaviour
changed (
github_search_code). - Don't clone the repo unless a single answer genuinely needs cross-file traces
no MCP tool can give — most don't. If it truly needs a full audit, say so and
recommend
<botMention> review(which routes topr-review) rather than blowing the cap.
3. Reply with one comment
github_add_issue_comment (PRs accept issue comments here). Keep it tight:
- Lead with the answer — yes / no / it depends. Don't bury it.
- Cite
path:line— clickable in the GitHub UI. - 3–8 sentences or a short bulleted list. No headings.
- If it's unanswerable from the PR alone, say so and name the specific information you'd need.
What the bot can and can't do on a PR
Maintainers ask about this in comments, so state it from these facts — never
improvise a limitation. botMention in the Context block is this deployment's
handle; use it in every command you suggest, never a hardcoded name.
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.
- 13d ago Changed · +28 lines 6c3929d1fef4
- 1mo ago First seen · 68 lines · 41 tokens per session scan A 42c7e4865eb7
pr-comment is a skill published in the GitHub repository nearform/lastlight (39 stars, last pushed 8d ago), licensed MIT. It adds 41 tokens to every session and 1,147 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
address_pr_comments
First, check the branch {{ BRANCHNAME }} and read the diff against the main branch to understand the purpose.
open-code-review
Performs AI-powered code review on Git changes using the ocr CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply…
github
A writing guide for GitHub issues, pull requests, code reviews, and release notes in Zhin projects. GitHub is a service where teams track bugs, discuss changes, review code, and publish project updates.
parallel-pr-review
Use when asked to "review the open PRs", review a batch or stack of pull requests, or run a recurring PR-review pass on a repo — especially with many PRs, stacked branches, conflicts, or security-sensitive changes. Covers grouping, fan-out to review subagents, verdict synthesis, and posting.
review-readiness
PR readiness dashboard — tracks which reviews have been completed per branch and gates merge decisions. Shows code review, tests, security, QA, and linting status.
codeflow-maintainer
OpenClaw-only maintainer PR workflow modes and skills. For OpenCoven/coven PR creation, redirect to skills/pr-agent, the Coven PR Readiness Agent.