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-resourcenpx skills add konglong87/superPM --skill pm-resourcegit 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-resource)<a href="https://agentmods.dev/skills/konglong87/superpm/pm-resource"><img src="https://agentmods.dev/badge/skills/konglong87/superpm/pm-resource.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 | $0.00053 | $0.03559 |
| Opus 5 | $0.00026 | $0.01780 |
| Sonnet 5 | $0.00011 | $0.00712 |
| Haiku 4.5 | $0.00005 | $0.00356 |
Grade A, and why
pm-resource scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 473 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preamble (run first)
bash "$(dirname "${BASH_SOURCE[0]}")/../../check-update.sh" 2>/dev/null || true
# 创建目录
mkdir -p docs/05-产品战略
# 检查是否有产品组合战略作为输入
if [ -f "docs/05-产品战略/产品组合战略.md" ]; then
echo "✅ 检测到产品组合战略文档,将基于此进行资源分配"
else
echo "⚠️ 未检测到产品组合战略文档,建议先执行 /pm-portfolio"
fi
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: 读取前置数据
优先读取:
docs/05-产品战略/产品组合战略.md
如果文件不存在,提示用户:
⚠️ 未找到产品组合战略文档
您可以选择: A) 先执行 /pm-portfolio 进行产品组合分析 B) 手动输入产品列表(快速模式)
步骤 2: 盘点可用资源
询问方式:使用 AskUserQuestion 逐个询问
问题 1: 研发团队规模
使用 AskUserQuestion 询问:
请问研发团队总人数?
A) 10人以下(小团队) B) 10-30人(中小团队) C) 30-50人(中型团队) D) 50-100人(大型团队) E) 100人以上(超大型团队) F) 其他(请手动输入)
问题 2: 可投入资源比例
本季度可投入新产品/项目的研发资源比例?
A) <20%(主要维护现有产品) B) 20-40%(小部分资源可投入新项目) C) 40-60%(资源较充足) D) 60-80%(重点投入新项目) E) >80%(全力投入新产品)
问题 3: 关键角色配置
团队中关键角色的配置情况?
逐个询问:
- 产品经理人数:[数字]
- 前端工程师人数:[数字]
- 后端工程师人数:[数字]
- 测试工程师人数:[数字]
- 运维工程师人数:[数字]
- 设计师人数:[数字]
问题 4: 资源约束条件
当前资源分配面临的主要约束是?(可多选)
A) 人力不足 B) 预算限制 C) 时间紧迫 D) 技术能力不足 E) 其他(请手动输入)
步骤 3: 产品资源需求评估
根据步骤1读取的产品列表,逐个评估资源需求:
针对每个产品询问:
评估项 1: 资源需求量
{产品名称}本季度需要的研发人力?
A) 极高(需要团队主力投入) B) 高(需要大量人力) C) 中(需要适中人力) D) 低(少量人力即可) E) 维护模式(仅需维护人力)
评估项 2: ROI预期
{产品名称}投入产出比(ROI)预期如何?
A) 极高ROI(投入1元,产出>10元) B) 高ROI(投入1元,产出5-10元) C) 中ROI(投入1元,产出2-5元) D) 低ROI(投入1元,产出<2元) E) 暂无ROI(战略投资期)
评估项 3: 时间紧迫性
{产品名称}的上线时间紧迫性?
A) 极紧迫(必须本季度上线) B) 紧迫(下季度必须上线) C) 适中(半年内上线即可) D) 不紧迫(一年内上线即可) E) 无明确时间要求
评估项 4: 风险等级
{产品名称}的开发风险等级?
A) 高风险(技术难度大、不确定性高) B) 中风险(有一定技术挑战) C) 低风险(技术成熟、风险可控) D) 极低风险(常规开发)
步骤 4: 资源分配决策
决策逻辑:
- 优先级评分模型
每个产品计算优先级得分:
优先级得分 = ROI得分 × 0.4 + 时间紧迫性得分 × 0.3 + 战略重要性得分 × 0.3 - 风险扣分
- 资源分配矩阵
| 优先级 | 资源占比 | 说明 |
|---|---|---|
| P0(最高) | 30-40% | 必须完成的核心项目 |
| P1(高) | 20-30% | 重要项目,保证交付 |
| P2(中) | 10-20% | 次要项目,按资源情况调整 |
| P3(低) | <10% | 探索性项目,资源充足时执行 |
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.
- 5d ago First seen · 473 lines · 53 tokens per session scan A c160cfd0ec6c
pm-resource is a skill published in the GitHub repository konglong87/superPM (61 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 3,559 once invoked, about $0.0003 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.
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