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/davidyichengwei/agency/code-reviewnpx skills add davidYichengWei/Agency --skill code-reviewgit clone --depth 1 https://github.com/davidYichengWei/AgencyWrote 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/davidyichengwei/agency/code-review)<a href="https://agentmods.dev/skills/davidyichengwei/agency/code-review"><img src="https://agentmods.dev/badge/skills/davidyichengwei/agency/code-review.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00063 | $0.01364 |
| Opus 5 | $0.00032 | $0.00682 |
| Sonnet 5 | $0.00013 | $0.00273 |
| Haiku 4.5 | $0.00006 | $0.00136 |
Grade A, and why
code-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 4d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Workflow
- Determine scope: gather changed files, PR/task intent, spec path, current task
- Pre-review skip: exit early for doc-only / config-only / trivial diffs
- Dispatch reviewers: 5 parallel specialist subagents
- Validator pass: 1 validator subagent per finding, dispatched in parallel — always runs, no short-circuit
- Dedup: merge confirmed findings that share file:line±3, severity, and fix
- Verdict + report
Step 1 — Determine scope
Collect before dispatching anything:
- Changed files from
git diff/gh pr diff(plus key context files: callers, interfaces, related modules) - Intent: PR title + description (
gh pr view) OR current task from.agent/*/plan.md+tasks.md - Spec: path to
docs/design-docs/<module>/<feature>/spec.mdif the active task references one - Size metrics: file count, total lines changed (used for sanity logging only)
Step 2 — Pre-review skip
Emit SKIPPED: <reason> and stop if ANY holds:
- All changed files match
docs/**,*.md,*.txt - Changes are limited to
CMakeLists.txt,.ci/**, config templates, licenses, generated files - Single file, <10 lines changed, and the change is obviously mechanical (rename, comment-only, whitespace, import reorder)
- PR is marked draft / WIP
Step 3 — Dispatch reviewers in parallel
Spawn all five in one message:
reviewer-perfreviewer-robustnessreviewer-standardsreviewer-specreviewer-proof-obligations
Each reviewer receives this prompt block:
Review the following code changes within your focus area.
[Scope]
Changed files: {files}
Context files: {callers, interfaces, related code}
[Intent]
PR / task: {pr_intent — from PR description or current task}
Spec: {spec path or N/A}
Current task: {task description or N/A}
Use [Intent] to distinguish intentional changes from regressions. If the diff
matches the stated intent, it is not an issue even if the old code was different.
[Severity]
- P0: Must fix before merge (correctness bug, crash, data corruption, critical spec deviation)
- P1: Should fix (specific conditions, contained impact, clear risk)
- P2: Improvement suggestion (no correctness/stability impact)
[Output format]
For each finding:
file:line — <one-line description>
severity: P0 | P1 | P2
confidence: 0-100 (your initial estimate; the validator will re-score)
why: <one-sentence rationale>
(optional) repro-hint: <failing input or execution path, if you already have one>
Only report issues in your focus area. If you spot something outside your area,
add a one-line handoff note (not a finding).
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.
- 4d ago First seen · 152 lines · 63 tokens per session scan A 98f3ab02f59f
code-review is a skill published in the GitHub repository davidYichengWei/Agency (5 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 1,364 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
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…