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 agentmods add commands/data-wise/claude-plugins/overviewgit clone --depth 1 https://github.com/Data-Wise/claude-pluginsWhat 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 | $0.00000 | $0.00756 |
| Opus 5 | $0.00000 | $0.00378 |
| Sonnet 5 | $0.00000 | $0.00151 |
| Haiku 4.5 | $0.00000 | $0.00076 |
Grade A, and why
overview scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Distribution** (2): Homebrew formulas, curl installers How it starts
The opening of the file, as written. The whole thing — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Commands Overview
TL;DR (30 seconds)
- What: 74 commands organized into 9 categories (Smart, Docs, Site, Code, Git, CI, Architecture, Distribution, Planning)
- Why: One plugin handles your entire development workflow from docs to deployment
- How: Use
/craft:hubto discover all commands by category- Next: Start with
/craft:dofor AI-powered task routing or/craft:checkfor pre-flight validation
Craft provides 74 commands across 9 categories for full-stack development workflows.
Command Categories
🎯 Smart Commands (4)
Universal commands with AI-powered routing:
/craft:do <task>- Universal task router/craft:orchestrate <task> [mode]- Enhanced orchestrator v2.1/craft:check [--for]- Pre-flight checks/craft:help [topic]- Context-aware help
📚 Documentation Commands (13)
Smart documentation generation and validation:
- Super Commands:
update,sync,check - NEW:
/craft:docs:website- ADHD-friendly enhancement - Specialized:
api,changelog,guide,demo,mermaid
🌐 Site Commands (12)
Full documentation site management:
/craft:site:create- Wizard with 8 ADHD-friendly presets- Navigation & audit:
nav,audit,consolidate - Management:
status,update,deploy
💻 Code & Testing Commands (12)
Development workflow tools:
- Linting:
/craft:code:lint [mode] - Testing:
/craft:test:run [mode] - Debugging:
/craft:code:debug - Refactoring:
/craft:code:refactor
🔀 Git & CI Commands (12)
Version control and continuous integration:
- Git:
worktree,sync,clean,recap,branch - CI:
detect,generate,validate
📦 Other Categories
- Architecture (7): System design, tech stack analysis
- Distribution (2): Homebrew formulas, curl installers
- Planning (3): Feature planning, sprints, roadmaps
- Discovery (1): Command hub
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.
- yesterday First seen · 99 lines · 0 tokens per session scan A dcacac6c9a34
overview is a command published in the GitHub repository Data-Wise/claude-plugins (7 stars, last pushed 5d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 756 tokens. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.