Borrowing it
Nothing to install: this file belongs to TalonT-Org/AutoSkillit. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/TalonT-Org/AutoSkillit/main/.claude/skills/make-arch-diag/SKILL.mdgit clone --depth 1 https://github.com/TalonT-Org/AutoSkillitWrote 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/talont-org/autoskillit/make-arch-diag)<a href="https://agentmods.dev/skills/talont-org/autoskillit/make-arch-diag"><img src="https://agentmods.dev/badge/skills/talont-org/autoskillit/make-arch-diag.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 5.1 | $0.00033 | $0.02236 |
| Opus 5 | $0.00016 | $0.01118 |
| Sonnet 5 | $0.00007 | $0.00447 |
| Haiku 4.5 | $0.00003 | $0.00224 |
Grade A, and why
make-arch-diag 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.
How it starts
The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Make-Arch-Diag: Architecture Diagram Generation
Creates comprehensive architecture diagrams for selected components or systems using mermaid syntax.
When to Use
- Documenting a new feature or component
- Updating architecture documentation after changes
- Onboarding new team members
- Explaining complex system interactions
- Before making significant architectural changes
Critical Constraints
ALWAYS:
- Ask user which component/system to diagram
- Use the
/mermaidskill for diagram creation - Include multiple views (data flow, component structure, sequence diagrams)
- Save diagrams to
temp/make-arch-diag/{component-name}/ - Use consistent color coding across all diagrams
NEVER:
- Create diagrams without understanding the code
- Skip reading the actual implementation
- Use generic placeholder names
- Create diagrams that contradict the code
Workflow
Step 1: Component Selection
Ask the user which area they want diagrammed:
Which component or system would you like to diagram?
Examples:
- Authentication system
- Database layer
- API endpoints
- Message queue processing
- State management
- Specific feature (e.g., "user registration flow")
Please specify the component/system:
Step 2: Scope Definition
Based on user input, determine:
- Boundaries: What's in scope vs out of scope
- Level of Detail: High-level architecture vs detailed implementation
- Audience: Developers, architects, stakeholders
Step 3: Code Exploration
Investigate the codebase:
- Find entry points (main, CLI, API routes)
- Trace execution flows
- Identify components and their relationships
- Map data flows
- Document external dependencies
Step 4: Diagram Types Selection
Choose appropriate diagram types:
Component Diagram (Always include)
- Shows major components and their relationships
- Good for: Understanding system structure
Data Flow Diagram (Include if data transformation is central)
- Shows how data moves through the system
- Good for: Understanding pipelines, ETL, processing
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 · 364 lines · 33 tokens per session scan A a83a286f76e4
make-arch-diag is a skill published in the GitHub repository TalonT-Org/AutoSkillit (5 stars, last pushed 9d ago), licensed MIT. It adds 33 tokens to every session and 2,236 once invoked, about $0.0002 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
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
babysit-pr
Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…