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 skills add porcupine-md/jonggrang --skill reviewing-architecturegit clone --depth 1 https://github.com/porcupine-md/jonggrangWrote 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/porcupine-md/jonggrang/reviewing-architecture)<a href="https://agentmods.dev/skills/porcupine-md/jonggrang/reviewing-architecture"><img src="https://agentmods.dev/badge/skills/porcupine-md/jonggrang/reviewing-architecture/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/porcupine-md/jonggrang/reviewing-architecture"><img src="https://agentmods.dev/badge/skills/porcupine-md/jonggrang/reviewing-architecture.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00025 | $0.00364 |
| Opus 5 | $0.00013 | $0.00182 |
| Sonnet 5 | $0.00005 | $0.00073 |
| Haiku 4.5 | $0.00003 | $0.00036 |
Grade A, and why
reviewing-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 11d 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.
What it actually says
Reviewing Architecture (Eng Review)
Role Constraints: Lead (Write/Bash access allowed).
File Access: Do NOT use literal placeholders for file paths. Use the glob tool to search for the active feature directory under .jonggrang/.output/features/.
Objective
Act as an Engineering Manager to lock in the execution plan. Review architecture, data flow, edge cases, test coverage, and performance.
Execution Steps
- Gather Context: Use
globandreadto find and review the feature'spitch.md,strategy-review.md, and any existing technical drafts in the active feature directory under.jonggrang/.output/features/. - Review Dimensions:
- Architecture & Data Flow: Does the data model support the feature? Are DB queries optimized?
- Edge Cases & Error Handling: What happens when APIs fail, inputs are malformed, or state is lost?
- Test Coverage: What is the testing strategy (unit, integration, E2E)?
- Performance: Are there N+1 query risks? Are assets optimized?
- Security: Are inputs sanitized? Are permissions checked properly?
- Iterative Refinement: Discuss identified technical gaps with the user and propose opinionated recommendations.
- Save Architecture Plan: Once finalized, use the
writetool to output the finalized technical decisions toarchitecture-review.mdin the active feature directory.
Completion Signal
When the architecture plan is finalized and saved, output exactly:
ARCHITECTURE_REVIEW_COMPLETE
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.
- 11d ago First seen · 32 lines · 25 tokens per session scan A fea07a2fd986
reviewing-architecture is a skill published in the GitHub repository porcupine-md/jonggrang (11 stars, last pushed 3d ago), licensed MIT. It adds 25 tokens to every session and 364 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 2026-08-30.
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