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/rito-w/claude-code-best-practice-zh/plangit clone --depth 1 https://github.com/Rito-w/claude-code-best-practice-zhWrote 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/commands/rito-w/claude-code-best-practice-zh/plan)<a href="https://agentmods.dev/commands/rito-w/claude-code-best-practice-zh/plan"><img src="https://agentmods.dev/badge/commands/rito-w/claude-code-best-practice-zh/plan.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 | $0.00007 | $0.02712 |
| Opus 5 | $0.00003 | $0.01356 |
| Sonnet 5 | $0.00001 | $0.00542 |
| Haiku 4.5 | $0.00001 | $0.00271 |
Grade A, and why
plan 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 4d 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.
This is a copy
100% identical to plan — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 417 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST parse the user input to extract the feature slug (the folder name in rpi/).
Purpose
This command creates comprehensive planning documentation for a feature request. It generates detailed specifications, technical design, and implementation plans in the feature's RPI folder.
Prerequisites:
- Feature folder exists at
rpi/{feature-slug}/ - Research completed with GO recommendation (
rpi/{feature-slug}/research/RESEARCH.mdexists)
Output Location: All files saved to rpi/{feature-slug}/plan/
This is Step 3 of the RPI Workflow (after Research approves with GO).
Outline
- Load Context: Read research report and project constitution (if exists)
- Understand Requirements: Parse feature scope and requirements
- Analyze Technical Requirements: Review architecture and dependencies
- Design Architecture: Create high-level architecture and API contracts
- Break Down Implementation: Create phased task breakdown
- Generate Documentation: Create structured documentation files
- Validate Output: Ensure all quality gates pass
- Report Completion: Provide summary and next steps
Phases
Phase 0: Load Context
Prerequisites: Feature slug provided
Process:
-
Verify research completed:
- Check
rpi/{feature-slug}/research/RESEARCH.mdexists - Verify GO recommendation (warn if NO-GO or CONDITIONAL)
- Check
-
Read research findings:
- Extract product analysis
- Extract technical discovery
- Extract technical feasibility assessment
- Note risks and constraints
-
Load project constitution (if exists):
- Look for a constitution or principles document in the repository
- Extract relevant constraints and preferences
Outputs:
- Research summary
- Constitutional context (if found)
- Planning constraints
Validation:
- Research report exists
- GO recommendation confirmed
- Constitution loaded (if exists)
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.
- 4d ago First seen · 417 lines · 7 tokens per session scan A 1417e095d66c
plan is a command published in the GitHub repository Rito-w/claude-code-best-practice-zh (10 stars, last pushed 2mo ago), licensed MIT. It adds 7 tokens to every session and 2,712 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to plan, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.
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.