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/davidruzicka/mcp4openapi/review-plan-before-implementationnpx skills add davidruzicka/mcp4openapi --skill review-plan-before-implementationgit clone --depth 1 https://github.com/davidruzicka/mcp4openapiWrote 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/davidruzicka/mcp4openapi/review-plan-before-implementation)<a href="https://agentmods.dev/skills/davidruzicka/mcp4openapi/review-plan-before-implementation"><img src="https://agentmods.dev/badge/skills/davidruzicka/mcp4openapi/review-plan-before-implementation.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 | $0.00054 | $0.00859 |
| Opus 5 | $0.00027 | $0.00430 |
| Sonnet 5 | $0.00011 | $0.00172 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
review-plan-before-implementation 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Implementation Plan Review
Review plans thoroughly before making code changes. For every issue or recommendation, explain concrete tradeoffs, give an opinionated recommendation, and ask for user input before choosing a direction.
Do not start implementation until the user explicitly approves implementation.
Engineering Preferences
- Flag DRY violations aggressively.
- Treat strong test coverage as mandatory.
- Target "engineered enough": avoid both fragile hacks and premature abstraction.
- Prefer handling more edge cases over fewer.
- Prefer explicit solutions over clever shortcuts.
Start Protocol
Ask the user to choose one mode first:
- BIG CHANGE
Review interactively section by section
(Architecture -> Code Quality -> Test -> Performance)
with at most 4 top issues per section. - SMALL CHANGE
Review interactively one key question per section.
Wait for mode selection before reviewing sections.
Review Sections
Review in this order:
- Architecture Review
- Code Quality Review
- Test Review
- Performance Review
Pause after each section and ask for user feedback before moving to the next section.
1) Architecture Review
Evaluate:
- Overall system design and component boundaries.
- Dependency graph and coupling concerns.
- Data flow patterns and potential bottlenecks.
- Scaling characteristics and single points of failure.
- Security architecture (auth, data access, API boundaries).
2) Code Quality Review
Evaluate:
- Code organization and module structure.
- DRY violations.
- Error handling patterns and missing edge cases.
- Technical debt hotspots.
- Over-engineered and under-engineered areas.
3) Test Review
Evaluate:
- Coverage gaps (unit, integration, e2e).
- Test quality and assertion strength.
- Missing edge case coverage.
- Untested failure modes and error paths.
4) Performance Review
Evaluate:
- N+1 queries and database access patterns.
- Memory-usage concerns.
- Caching opportunities.
- Slow or high-complexity code paths.
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 · 141 lines · 54 tokens per session scan A f6489baf6c88
review-plan-before-implementation is a skill published in the GitHub repository davidruzicka/mcp4openapi (0 stars, last pushed 16d ago), licensed MIT. It adds 54 tokens to every session and 859 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
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brainstorming
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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…