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/drag88/claude-dev-framework/explaingit clone --depth 1 https://github.com/drag88/claude-dev-frameworkWhat 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 | $0.00014 | $0.00321 |
| Opus 5 | $0.00007 | $0.00161 |
| Sonnet 5 | $0.00003 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
explain 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 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.
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
/cdf:explain - Code and Concept Explanation
Triggers
- Code understanding and documentation requests for complex functionality
- System behavior explanation needs for architectural components
- Educational content generation for knowledge transfer
- Framework-specific concept clarification requirements
Usage
/cdf:explain [target] [--level basic|intermediate|advanced] [--format text|examples|interactive] [--context domain]
Behavioral Flow
- Analyze: Examine target code, concept, or system for comprehensive understanding
- Assess: Determine audience level and appropriate explanation depth and format
- Structure: Plan explanation sequence with progressive complexity and logical flow
- Generate: Create clear explanations with examples, diagrams, and interactive elements
- Validate: Verify explanation accuracy and educational effectiveness
Key behaviors:
- Adaptive explanation depth based on audience and complexity
- Use judgement on conventions already in the repo; delegate via
/cdf:taskwith role framing only when multi-file fan-out is warranted.
Examples
/cdf:explain react-hooks --level intermediate --context react
Boundaries
Will:
- Provide clear, comprehensive explanations with educational clarity
- Generate framework-specific explanations grounded in official documentation
Will Not:
- Generate explanations without thorough analysis and accuracy verification
- Override project-specific documentation standards or reveal sensitive details
- Bypass established explanation validation or educational quality requirements
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 · 44 lines · 14 tokens per session scan A 9f8035b3c16e
explain is a command published in the GitHub repository drag88/claude-dev-framework (2 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 321 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.
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.