Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add pitimon/8-habit-ai-dev/plugin install 8-habit-ai-devWrote 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/pitimon/8-habit-ai-dev/design)<a href="https://agentmods.dev/skills/pitimon/8-habit-ai-dev/design"><img src="https://agentmods.dev/badge/skills/pitimon/8-habit-ai-dev/design.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 | $0.00042 | $0.03493 |
| Opus 5 | $0.00021 | $0.01747 |
| Sonnet 5 | $0.00008 | $0.00699 |
| Haiku 4.5 | $0.00004 | $0.00349 |
Grade A, and why
design 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 — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Step 2: Design (วางโครงสร้าง)
Habit: H8 — Find Your Voice | Anti-pattern: Letting AI decide architecture without human judgment
Process
- Read existing architecture and context contract: Check
CLAUDE.md,AGENTS.md,SPEC.md,DOMAIN.md,CONTEXT.md,CONTEXT-MAP.md,DESIGN.md,ARCHITECTURE.md,docs/agents/domain.md, and ADR directories. Understand current state and project vocabulary before proposing changes.
1b. Validate scope alignment: read the SKILL_OUTPUT:requirements block from docs/specs/<slug>/prd.md when persisted; otherwise recover scope_in / success criteria / risks from the PRD prose in context (non-persisted runs carry no block since v2.21.39, #375). Then verify:
- Proposed architecture decisions don't expand beyond
scope_in - Success criteria are achievable with the proposed design
- Identified
risksare addressed or accepted in design constraints
1c. Select the smallest safe pass level before producing design output:
| Pass level | Use when | Expected output |
|---|---|---|
| Scan | Small, bounded, exploratory, or unclear architecture impact | Compact architecture note, key constraints, open questions, and safe next step |
| Focus | One module, workflow, subsystem, integration, or boundary is in scope | Targeted decisions, local trade-offs, risks, and any needed ADRs |
| Full | Whole-system design, unclear ownership, 3+ interacting modules, persistence, authentication, payment, security, deployment, or future-agent handoff is needed | Full decision set, ADR coverage, risk register, human approvals, and handoff-ready constraints |
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 · 223 lines · 42 tokens per session scan A 7697e728161e
design is a skill published in the GitHub repository pitimon/8-habit-ai-dev (3 stars, last pushed 1mo ago), licensed MIT. It adds 42 tokens to every session and 3,493 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
fastapi
FastAPI best practices + Pydantic. Use when building or reviewing FastAPI APIs.
architect
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design".
backend
This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs".
documentation
Use when shipping features with public interfaces that lack docs, generating documentation, updating README files, writing API docs, creating architecture documentation, or when documentation is incomplete or outdated. Also use when adding breaking changes, implementing complex algorithms, or before shipping any phase…
auth-doctor
Diagnose and fix issues in existing auth setups. Scans environment, files, security, middleware, OAuth, database, and dangerous code patterns. Produces scored health report with actionable fixes.
python-patterns
Python backend patterns: layered architecture, async I/O, dependency injection, repository/service separation. TRIGGER when: creating routes, models, schemas, or services in a Python backend. SKIP: REST contract design (use api-design); schema/index tuning (use database-optimization). (Examples: FastAPI + SQLAlchemy +…