Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/tbthr/feishu-skill/feishu-prd-analyse)<a href="https://agentmods.dev/commands/tbthr/feishu-skill/feishu-prd-analyse"><img src="https://agentmods.dev/badge/commands/tbthr/feishu-skill/feishu-prd-analyse/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/tbthr/feishu-skill/feishu-prd-analyse"><img src="https://agentmods.dev/badge/commands/tbthr/feishu-skill/feishu-prd-analyse.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 | $0.00021 | $0.00623 |
| Opus 5 | $0.00010 | $0.00311 |
| Sonnet 5 | $0.00004 | $0.00125 |
| Haiku 4.5 | $0.00002 | $0.00062 |
Grade A, and why
feishu-prd-analyse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
You are analyzing a Product Requirements Document (PRD) from Feishu. Follow these steps:
执行步骤
1. 获取文档（推荐：使用 save 保存到临时文件）
⚠️ 重要：使用
cli.py save将文档保存到临时文件，避免文档内容注入 context。
python "${CLAUDE_PLUGIN_ROOT}/skills/feishu-analyst/scripts/cli.py" save "<FEISHU_URL>"
# 输出示例：
# {
# "document_id": "G85TdPCcTo91CYx4aYzcLKCnnFe",
# "title": "文档标题",
# "blocks_file": "/tmp/document_G85TdPCcTo91CYx4aYzcLKCnnFe_blocks.json",
# "markdown_file": "/tmp/document_G85TdPCcTo91CYx4aYzcLKCnnFe.md"
# }
2. 提取文档大纲
# 获取文档大纲
python "${CLAUDE_PLUGIN_ROOT}/skills/feishu-analyst/scripts/cli.py" outline /tmp/document_xxx_blocks.json
3. 应用 PRD 分析框架
Load the PRD checklist from skills/feishu-analyst/references/prd_checklist.md
Apply the systematic analysis framework across 4 dimensions:
- Ambiguity Check: Vague terms, metrics, timelines
- Logic Consistency: Contradictions, edge cases, preconditions
- Data Integrity: Type definitions, constraints, required fields
- Completeness: User stories, acceptance criteria, success metrics
⚠️ CRITICAL Requirements
- MUST read and analyze ALL content types, including:
- All text blocks (headings, paragraphs, lists)
- All tables (every row and column)
- All whiteboards/diagrams (flowcharts, mind maps, architecture diagrams)
- All images and screenshots
- All code blocks
- All embedded content
- Ensure no blocks are skipped or truncated
- Verify the document has been fully read before proceeding with analysis
- ALWAYS use cli.py save to save document to file, avoid loading content into context
输出格式
Generate a structured review with:
- Executive summary
- Critical findings (ambiguities, contradictions, data issues, gaps)
- Questions for product team
- Recommendations
- Overall assessment (Ready/Needs Revision/Major Gaps)
The user will provide a Feishu document URL (either /docx/ or /wiki/ format).
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 · 66 lines · 21 tokens per session scan A 73f0af9ca308
feishu-prd-analyse is a command published in the GitHub repository Tbthr/feishu-skill (3 stars, last pushed 6mo ago), licensed MIT. It adds 21 tokens to every session and 623 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
brand-generate
Generate an on-brand document from a saved Brand Profile.
cti-report
Render case deliverables — relationship graph (PNG/SVG/Mermaid) and a polished PDF/DOCX assessment. Usage: /cti-report [--graph|--pdf].
prose-review-docs
Reviews markdown documentation files or directories against the active prose style rules — the plugin's vendor-neutral baseline plus your organization's overlay when one is configured. Accepts a file path or directory (recursive). Runs prose-style-checker and optionally Vale. Supports --fix to auto-apply safe…
ppt-image2-editable-rebuild
Rebuild image2 or imagegen reference slides as editable PowerPoint decks.
render-figures
Compile all .tex and .typ figure files in a directory.
harness-onboarding
Generate a human-readable onboarding document from HARNESS.md, AGENTS.md, and REFLECTIONLOG.md — a friendly guide for new team members.