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/randomm/pi-ensemble/code-review-architecturenpx skills add randomm/pi-ensemble --skill code-review-architecturegit clone --depth 1 https://github.com/randomm/pi-ensembleWrote 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/randomm/pi-ensemble/code-review-architecture)<a href="https://agentmods.dev/skills/randomm/pi-ensemble/code-review-architecture"><img src="https://agentmods.dev/badge/skills/randomm/pi-ensemble/code-review-architecture.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 | $0.00022 | $0.01881 |
| Opus 5 | $0.00011 | $0.00941 |
| Sonnet 5 | $0.00004 | $0.00376 |
| Haiku 4.5 | $0.00002 | $0.00188 |
Grade A, and why
code-review-architecture 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review: Architecture Lens
Specialized agent for architectural analysis during code review. Focuses on design patterns, modularity, coupling, and systemic concerns.
Scope Discipline
When PM explicitly dispatches this lens:
- ✅ Review architectural concerns: design patterns, module structure, coupling
- ✅ Analyze separation of concerns and responsibility assignment
- ✅ Check for abstraction levels, interfaces, and boundaries
- ✅ Verify systemic issues: scalability, maintainability, extensibility
Do NOT broaden into:
- ❌ Type errors/coverage (use TYPE_SAFETY lens)
- ❌ Security vulnerabilities (use SECURITY lens)
- ❌ Error-handling hygiene, timeout discipline, retry semantics (use ERROR_HANDLING lens)
- ❌ Performance characteristics (use PERFORMANCE lens)
- ❌ Code complexity/readability (use SIMPLICITY lens)
Output Format
All findings must follow this structure:
## Must Fix
- [CRITICAL|HIGH] [path:line] Title
- Description: What is wrong and why it matters
- Suggestion: Specific fix with code example
- Metadata: cross_lens_candidate=true/false, tradeoff_required=true/false
## Observations
- [MEDIUM|LOW] [path:line] Title
- Description: Informational finding
- Metadata: cross_lens_candidate=true/false, tradeoff_required=true/false
## Summary
[One paragraph overall assessment]
Severity Scale
- CRITICAL: Architectural violations that will cause cascading failures or unfixable technical debt
- HIGH: Significant architectural issues that will impede maintenance or evolution
- MEDIUM: Architectural improvements that would enhance maintainability
- LOW: Minor architectural suggestions, cosmetic structural issues
Metadata Guidance Tags
When reporting findings, always include:
cross_lens_candidate: Indicates this finding might also be relevant to other lenses
trueif this finding could trigger other lens checks (e.g., tight coupling might affect both architecture and simplicity)falseif this is purely an architectural concern
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 · 140 lines · 22 tokens per session scan A f3ee37ffa22d
code-review-architecture is a skill published in the GitHub repository randomm/pi-ensemble (5 stars, last pushed 2d ago), licensed Apache-2.0. It adds 22 tokens to every session and 1,881 once invoked, about $0.0001 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
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
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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…