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/arraydude/agent-skills/validate-prnpx skills add arraydude/agent-skills --skill validate-prgit clone --depth 1 https://github.com/arraydude/agent-skillsWhat 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 | $0.00128 | $0.01051 |
| Opus 5 | $0.00064 | $0.00526 |
| Sonnet 5 | $0.00026 | $0.00210 |
| Haiku 4.5 | $0.00013 | $0.00105 |
Grade A, and why
validate-pr 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validate PR Comments
Validate AI-generated PR review comments on a pull request — determine which are accurate, which are low-priority noise, and which are hallucinations — by cross-referencing every comment against the actual diff.
When to Apply
Reference these guidelines when:
- The user wants AI/bot review comments on a PR checked for accuracy
- Triaging which review feedback is worth addressing before merge
- Separating genuine findings from hallucinations or misread intent
- Producing a prioritized action list from a noisy automated review
Prerequisite: the gh CLI must be installed and authenticated.
Rule Categories by Priority
| Priority | Category | Impact | Prefix |
|---|---|---|---|
| 1 | Setup & Input | CRITICAL | setup- |
| 2 | Data Gathering | CRITICAL | fetch- |
| 3 | Validation | CRITICAL | validate- |
| 4 | Output | HIGH | output- |
Quick Reference
1. Setup & Input (CRITICAL)
setup-gh-cli- Verify theghCLI is installed and authenticated before anything elsesetup-resolve-pr- Resolve the PR from the user's message (number/URL) or fall back to the current branch
2. Data Gathering (CRITICAL)
fetch-pr-data- Fetch comments, reviews, body, title, and files in onegh pr view --jsoncallfetch-complete-coverage- Also pull inline review-thread comments; review ALL of them, never a sample
3. Validation (CRITICAL)
validate-against-diff- Cross-reference each comment against the real diff and referenced filesvalidate-hallucination- Classify each comment: Valid / Low Priority / Hallucination / Addressedvalidate-worth-addressing- Judge whether a technically-true comment is actually worth the change
4. Output (HIGH)
output-summary-table- Present a priority-sorted table with fixed assessment labelsoutput-followup-details- Expand a single item (comment ID, assessment, verdict) on request
Core Workflow
- Setup — Confirm
ghis available and authenticated; resolve which PR to validate. - Fetch — Pull all PR data plus inline review comments; count them so nothing is dropped.
- Validate — For each comment, cross-reference the diff, decide hallucination vs. valid, and weigh whether it is worth addressing.
- Report — Emit the priority-sorted summary table, then expand any item the user asks about.
What ships with it
10 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.
- AGENTS.md 14 KB
- rules/fetch-complete-coverage.md 1.5 KB
- rules/fetch-pr-data.md 1.3 KB
- rules/output-followup-details.md 1.6 KB
- rules/output-summary-table.md 1.9 KB
- rules/setup-gh-cli.md 1.4 KB
- rules/setup-resolve-pr.md 1.7 KB
- rules/validate-against-diff.md 1.6 KB
- rules/validate-hallucination.md 1.8 KB
- rules/validate-worth-addressing.md 1.5 KB
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 · 102 lines · 128 tokens per session scan A 2666169729b9
validate-pr is a skill published in the GitHub repository arraydude/agent-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 128 tokens to every session and 1,051 once invoked, about $0.0006 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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