Borrowing it
Nothing to install: this file belongs to MDGrey33/claude_mind. 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/MDGrey33/claude_mind/main/.claude/skills/architecture/SKILL.mdgit clone --depth 1 https://github.com/MDGrey33/claude_mindWrote 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/mdgrey33/claude_mind/architecture)<a href="https://agentmods.dev/skills/mdgrey33/claude_mind/architecture"><img src="https://agentmods.dev/badge/skills/mdgrey33/claude_mind/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 5.1 | $0.00021 | $0.00482 |
| Opus 5 | $0.00010 | $0.00241 |
| Sonnet 5 | $0.00004 | $0.00096 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
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 6d 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
Architecture Skill
Design sound technical architecture that is scalable, maintainable, and secure.
When to Use
- Designing new system components
- Creating database schemas
- Defining API contracts
- Making technology decisions
- Writing Architecture Decision Records
Process
- Analyze Requirements - Understand core technical challenges
- Design Components - Define system architecture and interactions
- Model Data - Create database schemas with relationships
- Design APIs - Define RESTful endpoints and contracts
- Document Decisions - Create ADRs for major choices
ADR Template
# ADR-[NUMBER]: [Title]
**Status**: Proposed | Accepted | Rejected
**Date**: [YYYY-MM-DD]
## Context
[Why this decision is needed]
## Decision
[What was decided]
## Consequences
- Positive: [Benefits]
- Negative: [Trade-offs]
## Alternatives Considered
[Other options and why not chosen]
Data Model Template
## Entity: [Name]
| Field | Type | Constraints | Description |
|-------|------|-------------|-------------|
| id | uuid | PK, not null | Unique identifier |
### Relationships
- has_many: [Entity]
- belongs_to: [Entity]
### Indexes
- [fields]: For [query pattern]
API Endpoint Template
## [METHOD] /api/v1/[path]
**Purpose**: [Description]
**Auth**: Required/Optional
### Request
- Headers: Authorization, Content-Type
- Body: { field: type }
- Validation: [Rules]
### Response
- 200: { data: {...} }
- 400: { error: {...} }
- 401/403/404/500: [Error formats]
Quality Checklist
- Scalable design (horizontal scaling possible)
- Security considered (auth, validation, encryption)
- Performance targets defined
- Error handling strategy
- Follows project conventions
- ADRs for major decisions
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.
- 6d ago First seen · 93 lines · 21 tokens per session scan A f1760dd9c0e8
architecture is a skill published in the GitHub repository MDGrey33/claude_mind (2 stars, last pushed 8mo ago), licensed MIT. It adds 21 tokens to every session and 482 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.
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