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 skills/konglong87/superpm/pm-docsnpx skills add konglong87/superPM --skill pm-docsgit clone --depth 1 https://github.com/konglong87/superPMWrote 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/skills/konglong87/superpm/pm-docs)<a href="https://agentmods.dev/skills/konglong87/superpm/pm-docs"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-docs.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 | $0.00133 | $0.03640 |
| Opus 5 | $0.00067 | $0.01820 |
| Sonnet 5 | $0.00027 | $0.00728 |
| Haiku 4.5 | $0.00013 | $0.00364 |
Grade A, and why
pm-docs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 495 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preamble (run first)
bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
# 创建方案设计目录
mkdir -p docs/02-方案设计
# 检查前置文档
echo "📊 正在检查前置文档..."
if [ -f "docs/01-需求调研/MVP方案.md" ]; then
echo "✅ MVP方案 - 已找到"
else
echo "⏳ MVP方案 - 未找到"
fi
if [ -f "docs/01-需求调研/需求调研报告.md" ]; then
echo "✅ 需求调研报告 - 已找到"
else
echo "⏳ 需求调研报告 - 未找到"
fi
if [ -f "docs/01-需求调研/市场调研报告.md" ]; then
echo "✅ 市场调研报告 - 已找到"
else
echo "⏳ 市场调研报告 - 未找到"
fi
前置门禁
无论从哪个入口进入,都必须执行前置文档检查:
- 检查
docs/01-需求调研/中是否有 MVP方案(黄金路径的必要前置) - 如果有 MVP方案 → 读取文档,判断是否与当前用户描述的产品相关
- 相关 → 前置已满足,继续执行
- 不相关 → 停止,建议先完成前置流程
- 如果没有 MVP方案 → 停止,建议先执行
/pm-brainstorm→/pm-demand→/pm-mvp
不得在门禁不满足时生成文档。
跨 Agent 交互规则
当流程要求与用户交互时:
- 如果当前环境支持 AskUserQuestion,使用 AskUserQuestion(最佳体验)。
- 如果当前环境不支持 AskUserQuestion,必须用普通聊天消息提出同样问题。
- 一次只问一个问题。
- 提问后必须停止当前回合,等待用户回答(STOP and WAIT)。
- 不得在用户回答前生成文档、写入 docs。
- 已有 docs 文件不能替代本轮用户回答。
执行流程
步骤 1: 确定文档类型(主 agent - 用户交互)
使用 AskUserQuestion 询问:
您希望生成哪些文档?
A) 仅 PRD - 产品需求文档 B) 仅 BRD - 商业需求文档 C) 仅 MRD - 市场需求文档 D) PRD + BRD + MRD(全套文档,推荐) E) 让我推荐(根据项目状态自动选择)
💡 提示:选择"D"可并行生成全套文档,效率提升 3x
用户选择后,记录到变量 DOC_TYPES(数组)
步骤 2: 读取前置数据(主 agent)
读取所有可能需要的前置文档:
# 主 agent 一次性读取所有前置文档
required_docs=(
"docs/01-需求调研/MVP方案.md"
"docs/01-需求调研/需求调研报告.md"
"docs/01-需求调研/市场调研报告.md"
"docs/01-需求调研/确认需求清单.md"
"docs/01-需求调研/优先级排序报告.md"
)
for doc in "${required_docs[@]}"; do
if [ -f "$doc" ]; then
# 使用 Read 工具读取
echo "读取 $doc"
fi
done
构建上下文摘要(避免占用大量上下文):
提取关键信息:
- 产品名称
- 目标用户
- 核心功能
- MVP范围
- 市场数据
- 商业目标
将关键信息存储为结构化数据,准备传递给 subagent。
步骤 3: 并行派发 subagent 生成文档(核心优化)
优化说明:
- 主 agent 一次性派发多个 subagent
- 每个 subagent 负责生成一个文档
- 文档生成细节不占用主 agent 上下文
- 所有文档并行生成
3.1 构建 subagent 任务
如果用户选择"全套文档":
准备 3 个并行 subagent 任务:
[
{
"task_id": "generate_prd",
"doc_type": "PRD",
"required_data": [
"产品名称",
"目标用户",
"MVP功能列表",
"用户需求",
"优先级排序"
]
},
{
"task_id": "generate_brd",
"doc_type": "BRD",
"required_data": [
"产品名称",
"商业模式",
"市场数据",
"成本分析",
"盈利预测"
]
},
{
"task_id": "generate_mrd",
"doc_type": "MRD",
"required_data": [
"产品名称",
"市场调研数据",
"用户画像",
"竞品分析",
"市场机会"
]
}
]
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.
- 3d ago First seen · 495 lines · 133 tokens per session scan A 304bd1d6d9a1
pm-docs is a skill published in the GitHub repository konglong87/superPM (60 stars, last pushed 21d ago), licensed MIT. It adds 133 tokens to every session and 3,640 once invoked, about $0.0007 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 2026-08-30.
Other skills, from other repositories
deepsafe-scan
Preflight security scanner for AI coding agents — scans deployment config, skills/MCP servers, memory/sessions, and AI agent config files (hooks injection) for secrets, PII, prompt injection, and dangerous patterns. Runs 4 model behavior probes (persuasion, sandbagging, deception, hallucination). Supports LLM-enhanced…
douyin-upload-mcp-skill
通过抖音创作者平台(creator.douyin.com)发布视频和图文内容。首选调用 MCP 工具完成操作,MCP 无法满足时可运行 Skill 脚本兜底。禁止自行启动外部浏览器访问抖音。.
team-tasks
Coordinate multi-agent development pipelines using shared JSON task files. Use when dispatching work across dev team agents (code-agent, test-agent, docs-agent, monitor-bot), tracking pipeline progress, or running sequential/parallel workflows. Covers project init, task assignment, status tracking, agent dispatch via…
multi-search
智能多引擎搜索,自动检测网络环境并按优先级切换:DuckDuckGo -> Tavily -> Bing API -> Bing爬虫。支持自动配额管理和网络缓存。Invoke when user needs web search with automatic engine selection and network adaptation.
meeting-note-summarizer
Turn meeting notes or transcripts into factual summaries, decisions, questions, and action items. Use when a user wants a concise recap or needs explicit owners and deadlines extracted without filling in missing details.
daily-standup-journal
Generate concise daily standups, reflection prompts, and weekly retrospectives for individuals or teams. Use for planning a day, surfacing blockers, reviewing user-provided entries, or drafting a check-in without assuming prior history.