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/theagenticguy/opencodehub/codehub-pr-reviewnpx skills add theagenticguy/opencodehub --skill codehub-pr-reviewgit clone --depth 1 https://github.com/theagenticguy/opencodehubWhat 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 | $0.00064 | $0.02571 |
| Opus 5 | $0.00032 | $0.01286 |
| Sonnet 5 | $0.00013 | $0.00514 |
| Haiku 4.5 | $0.00006 | $0.00257 |
Grade A, and why
codehub-pr-review 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.
This is a copy
100% identical to opencodehub-pr-review — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Review with OpenCodeHub
When to Use
- "Review this PR."
- "What does PR #42 change?"
- "Is this safe to merge?"
- "What's the blast radius of this PR?"
- "Are there missing tests for this PR?"
- "Did this PR introduce a copyleft / unknown license?"
- Reviewing someone else's code changes before merge.
The Golden Workflow
1. mcp__codehub__verdict({ base, head }) → 5-tier merge decision
2. mcp__codehub__list_findings_delta({ base }) → New / fixed / unchanged / updated findings
3. mcp__codehub__detect_changes({ scope: "compare", base_ref }) → Changed symbols + affected flows
4. For each non-trivial changed symbol:
mcp__codehub__impact({ name, direction: "upstream" }) → Blast radius + confidenceBreakdown
5. mcp__codehub__license_audit → Copyleft / unknown / proprietary tiers
6. mcp__codehub__scan (opt-in) → Fresh scanner run — spawns processes
7. Write the review using the output template below
If the context envelope warns the index is stale, run
codehub analyzebefore starting — stale graphs produce stale verdicts.
Checklist
- [ ] Fetch the PR diff (gh pr diff <n> or git diff <base>...<head>)
- [ ] mcp__codehub__verdict — start here; it aggregates the review signal
- [ ] Capture the verdict tier, top drivers, and blockers
- [ ] mcp__codehub__list_findings_delta — new findings since the baseline
- [ ] mcp__codehub__detect_changes — map the diff to affected processes
- [ ] mcp__codehub__impact on each non-trivial changed symbol
- [ ] Inspect confidenceBreakdown per impact — prefer confirmed edges for breakage claims
- [ ] mcp__codehub__license_audit — flag copyleft or unknown license changes
- [ ] (optional) mcp__codehub__scan to re-run scanners if the baseline is stale
- [ ] Write the review in the output template below
Tools
mcp__codehub__verdict — the starting point
mcp__codehub__verdict({ base: "main", head: "HEAD", repo: "my-app" })
→ tier: "auto_merge" | "single_review" | "dual_review" | "expert_review" | "block"
→ drivers: [{ signal, weight, evidence }] // top reasons the tier was chosen
→ blockers: [...] // non-empty only for tier=block
→ next_action: "merge" | "request review from X" | "add tests for Y" | "fix finding Z"
→ exit_code: 0 | 1 | 2
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 · 247 lines · 64 tokens per session scan A b04cfa85eeee
codehub-pr-review is a skill published in the GitHub repository theagenticguy/opencodehub (3 stars, last pushed 20d ago), licensed Apache-2.0. It adds 64 tokens to every session and 2,571 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to opencodehub-pr-review, differing in 2 lines, and is treated as a copy.
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…