Borrowing it
Nothing to install: this file belongs to Rito-w/claude-code-best-practice-zh. 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/Rito-w/claude-code-best-practice-zh/main/.claude/commands/workflows/best-practice/workflow-claude-commands.mdgit 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/workflow-claude-commands)<a href="https://agentmods.dev/commands/rito-w/claude-code-best-practice-zh/workflow-claude-commands"><img src="https://agentmods.dev/badge/commands/rito-w/claude-code-best-practice-zh/workflow-claude-commands/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/rito-w/claude-code-best-practice-zh/workflow-claude-commands"><img src="https://agentmods.dev/badge/commands/rito-w/claude-code-best-practice-zh/workflow-claude-commands.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00011 | $0.01715 |
| Opus 5 | $0.00005 | $0.00857 |
| Sonnet 5 | $0.00002 | $0.00343 |
| Haiku 4.5 | $0.00001 | $0.00171 |
Grade A, and why
workflow-claude-commands 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 9d 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 workflow-claude-commands — 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow Changelog — Commands Report
You are a coordinator for the claude-code-best-practice project. Your job is to launch a research agent, wait for its results, and present a report about drift in the Commands Reference report (best-practice/claude-commands.md).
This workflow checks for exactly two types of drift:
- Frontmatter fields — any field added or removed in the official docs
- Official commands — any built-in slash command added or removed
Versions to check: $ARGUMENTS (default: 10 if empty or not a number)
This is a read-then-report workflow. Launch the agent, merge findings, and produce a report. Only take action if the user approves.
Phase 1: Launch Research Agent
Spawn the workflow-claude-commands-agent with this prompt:
Research the claude-code-best-practice project for commands report drift. Check the last $ARGUMENTS versions (default: 10).
Fetch these 2 external sources:
- Slash Commands Reference: https://code.claude.com/docs/en/slash-commands
- Changelog: https://github.com/anthropics/claude-code/blob/main/CHANGELOG.md
Then read the local report (
best-practice/claude-commands.md).Check for exactly two things:
- Frontmatter fields: Compare the official docs' supported command frontmatter fields against the report's Frontmatter Fields table. Flag any fields that were added or removed.
- Official commands: Compare the official docs' built-in slash commands list against the report's official commands table. Flag any commands that were added or removed. Also check if any command's tag or description has changed.
Phase 2: Read Previous Changelog Entries
While the agent is running, read changelog/best-practice/claude-commands/changelog.md to get the last 25 entries. Parse the priority actions to identify:
- Recurring items — issues that appeared before and are still unresolved
- New items — issues appearing for the first time
- Resolved items — previously flagged issues now fixed
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.
- 9d ago First seen · 141 lines · 11 tokens per session scan A 6404207c19db
workflow-claude-commands 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 11 tokens to every session and 1,715 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to workflow-claude-commands, differing in 0 lines, and is treated as a copy.
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.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.