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 OKHP3/skillz --skill software-architecture-analysisgit clone --depth 1 https://github.com/OKHP3/skillzWrote 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/okhp3/skillz/software-architecture-analysis)<a href="https://agentmods.dev/skills/okhp3/skillz/software-architecture-analysis"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/software-architecture-analysis/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/okhp3/skillz/software-architecture-analysis"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/software-architecture-analysis.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 | $0.00117 | $0.03019 |
| Opus 5 | $0.00059 | $0.01510 |
| Sonnet 5 | $0.00023 | $0.00604 |
| Haiku 4.5 | $0.00012 | $0.00302 |
Grade A, and why
software-architecture-analysis 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 7d 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.
This is a copy
100% identical to software-architecture-analysis — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Architecture Analysis — Codebase Reverse Engineering to Design Document
When to Use
- A reference implementation exists and you need to understand its architecture for design inspiration
- You need a PRD, design document, or specification for a system in the same problem space
- The output must be clean-room: zero source code samples copied from the reference codebase
- You're designing a system with different architectural constraints (local-first, privacy-first, self-hosted) than the reference
- You need to extract an implicit contract — the storage operations a codebase performs — to design a formal provider abstraction
- You need to assess architecture health, coupling, modularity, data ownership, distributed workflows, or readiness for a boundary change from repository evidence
Don't use for: Greenfield or proactive architecture design (route to software-architecture), direct code review, bug hunting, or security auditing. Route API/interface semantics to api-design-and-evolution, data-platform strategy to data-architect, implementation to the relevant engineering skill, deployment substrate to platform-engineering, and execution of an approved cross-system migration to migration-engineering.
Build Workflow
Phase 1: Clone + Map → Phase 2: Find Key Files → Phase 3: Map Architecture
↓
Phase 6: Constraint Redesign ← Phase 5: Write Spec ← Phase 4: Feature Inventory
↓
Phase 7: QA
Phase 1: Repository Cloning and Structure Mapping
Clone the target repository with a shallow clone:
git clone --depth=1 https://github.com/owner/repo /tmp/target-repo
Map the top-level directory structure. For each directory, identify:
- What language/framework it uses
- Whether it's frontend, backend, service, firmware, or support
- Whether it's a core component (business logic) or support (CI, docs, tooling)
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 7.4 KB
- README.md 2.5 KB
- references/architecture-characteristics-analysis.md 3.2 KB
- references/coupling-modularity-and-decomposition.md 3.7 KB
- references/data-ownership-and-workflow-analysis.md 3.0 KB
- references/interface-extraction-pattern.md 5.7 KB
- templates/architecture-health-assessment.md 2.5 KB
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.
- 7d ago First seen · 251 lines · 117 tokens per session scan A a79da8aa287d
software-architecture-analysis is a skill published in the GitHub repository OKHP3/skillz (3 stars, last pushed yesterday), licensed MIT. It adds 117 tokens to every session and 3,019 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to software-architecture-analysis, differing in 0 lines, and is treated as a copy.
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