architecture-docs

architecture-docs is a skill for Codex from jeremylongworth-source/AgentSkills. It costs 50 tokens per session (300 once invoked), scanned A, original, MIT.

A guide for documenting software architecture and ADRs. An ADR, or Architecture Decision Record, explains an important technical choice and its consequences.

In plain words
What is it for?
Use it to describe components, data flows, integrations, constraints, and decisions in software systems, repositories, libraries, or workflows.
Why use it?
It makes system structure, dependencies, tradeoffs, and open questions easier to understand without inventing details.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to describe components, data flows, integrations, constraints, and decisions in software systems, repositories, libraries, or workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jeremylongworth-source/agentskills/architecture-docs
Install

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.

Any agent
npx skills add jeremylongworth-source/AgentSkills --skill architecture-docs
Clone the repo
git clone --depth 1 https://github.com/jeremylongworth-source/AgentSkills

Made for: Codex.

Wrote 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.

agentmods badge for architecture-docs

README.md
[![agentmods](https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/architecture-docs.svg)](https://agentmods.dev/skills/jeremylongworth-source/agentskills/architecture-docs)
Your own site
<a href="https://agentmods.dev/skills/jeremylongworth-source/agentskills/architecture-docs"><img src="https://agentmods.dev/badge/skills/jeremylongworth-source/agentskills/architecture-docs.svg" alt="Measured on agentmods" height="20"></a>
Per session 50 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 300 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00050 $0.00300
Opus 5 $0.00025 $0.00150
Sonnet 5 $0.00010 $0.00060
Haiku 4.5 $0.00005 $0.00030

Measured 8d ago against content hash bc6098abe0dd, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

architecture-docs 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 8d 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.

skills/architecture-docs/SKILL.md · 46 lines

What it actually says

Architecture Docs

Core Workflow

  1. Identify the audience, system boundary, source of truth, and decision the doc supports.
  2. Read the relevant code, configs, diagrams, existing docs, and tests before describing architecture.
  3. Document structure, responsibilities, data flow, integration points, dependencies, constraints, and operational assumptions.
  4. For decisions, capture context, options considered, tradeoffs, decision, consequences, and review triggers.
  5. Separate current architecture from planned architecture.
  6. Include validation notes and open questions.

Safety Rules

  • Do not invent architecture, dependencies, guarantees, or operational behavior.
  • Do not expose sensitive infrastructure, secrets, private endpoints, or threat details in public docs.
  • Mark inferred architecture clearly when source evidence is incomplete.

Deliverable Shape

For architecture docs, provide:

  • Scope and audience
  • System overview
  • Components and responsibilities
  • Data or control flow
  • Key decisions and tradeoffs
  • Constraints and risks
  • Validation notes
  • Open questions

References

  • Read references/architecture-docs-checklist.md when writing architecture docs or ADRs.
Files

What ships with it

2 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.

Changes

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.

  1. 8d ago First seen · 46 lines · 50 tokens per session scan A bc6098abe0dd

Subscribe to this mod's changes

architecture-docs is a skill published in the GitHub repository jeremylongworth-source/AgentSkills (1 stars, last pushed 5d ago), licensed MIT. It adds 50 tokens to every session and 300 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.

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