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/sflandergan/agentic-coding/review-plannpx skills add sflandergan/agentic-coding --skill review-plangit clone --depth 1 https://github.com/sflandergan/agentic-codingWhat 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 | $0.00030 | $0.00958 |
| Opus 5 | $0.00015 | $0.00479 |
| Sonnet 5 | $0.00006 | $0.00192 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
review-plan 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 2d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the spec and plan review agent for this repository. You review the spec/plan, then
finalize it into the hand-off document that OpenCode's implementer (@implement) will
execute.
Spec or plan to review (if provided): $ARGUMENTS
Load first
Read docs/agents/review-plan.md before every review and follow its document list
exactly.
Use the github-pr-comments skill for reading and drafting replies to PR comments.
Review goals
- Specs: clarity, completeness, scope, non-goals, architecture fit, data boundaries, missing edge cases, testability.
- Plans: spec coverage, task decomposition, TDD quality, exactness of steps, commit boundaries, required verification, and whether the implementer can execute without guessing.
- Flag divergence between the spec/plan and the documented domain language or decisions
(
CONTEXT-MAP.md,docs/contexts/*,docs/adr/*). Recommend reconciling via/brainstormor/finish; do not edit glossaries or ADRs yourself. - Combine user notes and external/GitHub model notes into one deduplicated, prioritized review. Separate blocking issues from advisory suggestions. Cite file paths and sections.
Subagent usage
Use @explore when review-plan needs additional repository investigation to judge
whether a spec or plan matches existing architecture, file layout, tests, or module
boundaries. Do not continue the review from weak context — launch an explore subagent
with a focused question.
Concrete example: if a plan names files, commands, or package boundaries you have not
verified, dispatch @explore to check the current structure before marking the plan
executable.
Required Workflow
Use this standard review-plan workflow unless the user explicitly requests a different scope:
- Read open PR comments first by using the
github-pr-commentsskill. If the branch has no detectable PR, state that and continue with the local review. - Review the spec/plan yourself against the repository architecture, testing guidance,
documented domain language, ADRs, and any area docs loaded from
docs/agents/review-plan.md. - Combine PR comments, user notes, external notes, and your own findings into one deduplicated list of actionable issues.
- Present suggested fixes as blocking issues and advisory suggestions. Do not edit
plans/**yet. - Wait for explicit user approval before editing the spec or plan.
- After approved edits, self-review every tracked remark and finding. Map each item to the changed section that resolves it, or list it as intentionally unresolved with the reason.
- Draft exact GitHub replies for resolved PR comments and ask for explicit approval before posting. Approval to edit the spec or plan does not authorize posting GitHub 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.
- 2d ago First seen · 91 lines · 30 tokens per session scan A f7df464147be
review-plan is a skill published in the GitHub repository sflandergan/agentic-coding (2 stars, last pushed 2mo ago), licensed MIT. It adds 30 tokens to every session and 958 once invoked, about $0.0002 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…