Borrowing it
Nothing to install: this file belongs to jpicklyk/task-orchestrator. 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/jpicklyk/task-orchestrator/main/.claude/skills/review-quality/SKILL.mdgit clone --depth 1 https://github.com/jpicklyk/task-orchestratorWrote 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/jpicklyk/task-orchestrator/review-quality)<a href="https://agentmods.dev/skills/jpicklyk/task-orchestrator/review-quality"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/review-quality/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/jpicklyk/task-orchestrator/review-quality"><img src="https://agentmods.dev/badge/skills/jpicklyk/task-orchestrator/review-quality.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 | $0.00060 | $0.03412 |
| Opus 5.5 | $0.00024 | $0.01365 |
| Sonnet 5.5 | $0.00012 | $0.00682 |
| Haiku 4.5 | $0.00006 | $0.00341 |
Grade A, and why
review-quality 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 5d 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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Quality Framework
This skill defines what a reviewer must verify before implementation work advances to completion. It applies whether the reviewer is the orchestrator directly or a delegated subagent.
The review gate exists because implementation agents optimize for getting things working, not for verifying they built the right thing. Without a structured review checkpoint, planned work gets silently dropped, tests get written to pass rather than to verify, and unnecessary complexity accumulates. The review is where these failure modes get caught.
Critical separation of concerns: The reviewer must not be the same agent that wrote the code or the tests. An agent reviewing its own work will rationalize rather than evaluate. The reviewer reads, runs, and reports — it never fixes. If issues are found, they go back to the implementation agent for resolution.
This is the same principle the needs-test-author trait applies one step earlier, to
test authorship itself — the test author must not be the implementer, for the same
rationalize-not-evaluate reason. Verifying that separation actually held (see
"Independence verification" in Area 3) is this rule applied to test authorship, not an
optional extra.
Getting Started
The reviewer is given an MCP item ID. Use MCP tools and codebase access to gather what you need — do not expect context to be pre-loaded for you.
- Load the item's notes —
notes_readlist(itemId) names them, andnotes_readget(itemId,key) returns the planning note andimplementation-notes. The planning note's key depends on the item's schema:feature-summary(feature-implementation),task-scope(feature-task), ordiagnosis(bug-fix). - Read the changed files — use the implementation notes to identify which files were modified, then read them directly. Review the actual code, not just summaries.
- Run the test suite — execute the project's test command and capture the results. Do not assume tests pass because the implementation agent said they did.
- For items carrying the
needs-test-authortrait — load the trait'stest-planandtest-manifestnotes withnotes_readget(itemId,key), which carries the test author's own commit SHA range field, and obtain the orchestrator-provided per-child SHA table (Pre-SHA/Post-SHA/Test-Pre-SHA/ Test-Post-SHA) plus any declared orchestrator fixture-repair commit SHAs from the review handoff, for cross-checking. A trait-bearing item with notest-plannote is a blocking issue on its own — do not proceed to the Area 3 independence verification until the note exists.
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.
- 5d ago Changed · -1 lines 0351c2b9ad2c
- 12d ago Changed · +11 lines 461b06eef412
- 22d ago Changed · +9 lines 42aa4b59eb2d
- 28d ago Changed · +12 lines 00ebebef2450
- 1mo ago First seen · 241 lines · 60 tokens per session scan A ae062cf00468
review-quality is a skill published in the GitHub repository jpicklyk/task-orchestrator (210 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 3,412 once invoked, about $0.0002 per session on Opus 5.5. 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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agent-pipeline
Turn a review of code or docs into verified, actioned work with tiered agents. A cheap agent maps, a smart agent tags findings with predicted steps and a test written before any action, a skeptic verifies, a cheap agent acts in a sandbox, and the whole chain is reviewed afterwards with agent-review. Use for a sweep…
crap-analyzer
Use to produce a risk-based refactor + test plan for recently-changed code on a diff/branch/PR by computing CRAP (complexity × untested) on changed methods. Multi-language — TypeScript, JavaScript, Python, Java, Kotlin, Go, Ruby, C#, Rust, PHP — auto-discovers how the repo generates coverage. Triggers …
pre-pr
Prepare a Honcho change for a pull request to plastic-labs/honcho. Invoke before opening a PR, when drafting a PR body, when asked if a branch is PR-ready, or when filling the pull request template. Checks required tests and docs, then writes Description / Proofs / Fixes.
ork-verify
Verify that existing work is ready to merge, release, or hand off using an explicit evidence contract. Use when a request asks to verify, validate, prove, check readiness, run the relevant tests, or distinguish a claimed result from an observed one. Do not use to write missing tests or fix failures.
risk-based-code-review
Use when reviewing or verifying software changes before completion, release, merge, deployment, or acceptance, especially when the appropriate test depth is unclear or security, data, migrations, external interfaces, infrastructure, or user-visible behavior may be affected.