nexu is an open-source desktop client that connects an OpenClaw AI agent to messaging services such as WeChat, Feishu, Slack, and Discord. It is for people who want to chat with their agent from those channels using their own model credentials while keeping data on their computer, and the catalogue entries support its agent workflows.
Borrowing it
Nothing to install: this file belongs to nexu-io/nexu. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nexu-io/nexu/main/.agents/skills/process-pr-reviews/SKILL.mdgit clone --depth 1 https://github.com/nexu-io/nexuWrote 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/nexu-io/nexu/process-pr-reviews)<a href="https://agentmods.dev/skills/nexu-io/nexu/process-pr-reviews"><img src="https://agentmods.dev/badge/skills/nexu-io/nexu/process-pr-reviews/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/nexu-io/nexu/process-pr-reviews"><img src="https://agentmods.dev/badge/skills/nexu-io/nexu/process-pr-reviews.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 | $0.00093 | $0.02345 |
| Opus 5 | $0.00046 | $0.01172 |
| Sonnet 5 | $0.00019 | $0.00469 |
| Haiku 4.5 | $0.00009 | $0.00234 |
Grade A, and why
process-pr-reviews 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 10d 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 — 282 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process PR Reviews
This workflow supports both CodeRabbit and Codex PR review signals.
CodeRabbit Reviews
“Real review feedback” is strictly defined as:
- inline review comments
- not a review summary
- not a nitpick
Nitpick comments from CodeRabbit must always be ignored to avoid unnecessary noise.
There is no need to analyze the comment content itself.
Data sources
The CodeRabbit workflow only needs these two sources:
-
PR review comments
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/commentsThis is the authoritative source for real inline comments.
-
PR reviews
gh api --paginate repos/<owner>/<repo>/pulls/<pr_number>/reviewsThis is only used to identify and exclude review summaries / nitpick summaries. It is not used to extract the final result.
Do not treat these as primary sources:
gh pr view ...gh api repos/<owner>/<repo>/issues/<pr_number>/comments
Reason: they are not the authoritative source for actionable inline comments.
Workflow
0. Optional: fetch review thread IDs early if resolve/dismiss may be needed
If the user may ask you to resolve review conversations after triaging them, fetch review thread IDs as soon as you know the PR number:
gh api graphql -f query='query { repository(owner: "<owner>", name: "<repo>") { pullRequest(number: <pr_number>) { reviewThreads(first: 100) { nodes { id isResolved comments(first: 20) { nodes { databaseId path line author { login } body } } } } } } }'
This is not a primary source for actionable review feedback. It is only for mapping inline comments to resolvable thread IDs.
Recommendation:
- If the user only wants to view/list/count review feedback, this step is optional.
- If the user may want to resolve conversations, doing this early is usually more convenient because you can map comment
databaseId/path/lineto thread IDs in one pass.
1. Fetch inline comments
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.
- 10d ago First seen · 282 lines · 93 tokens per session scan A d101da943ca4
process-pr-reviews is a skill published in the GitHub repository nexu-io/nexu (3,265 stars, last pushed 4mo ago), licensed MIT. It adds 93 tokens to every session and 2,345 once invoked, about $0.0005 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.
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