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.
git clone --depth 1 https://github.com/lisihao/SolarWrote 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/agents/lisihao/solar/pm)<a href="https://agentmods.dev/agents/lisihao/solar/pm"><img src="https://agentmods.dev/badge/agents/lisihao/solar/pm/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/agents/lisihao/solar/pm"><img src="https://agentmods.dev/badge/agents/lisihao/solar/pm.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 | $0.00716 |
| Opus 5.5 | $0.00008 | $0.00286 |
| Sonnet 5.5 | $0.00004 | $0.00143 |
| Haiku 4.5 | $0.00002 | $0.00072 |
Grade A, and why
pm 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 1mo 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
@PM — 项目管理
任务路由
外部模型 (brain-router)
| 类型 | 牛马 | 角色 | 说明 |
|---|---|---|---|
| 需求分析 | deepseek-r1 | judge | 7.5分，深度拆解，验收标准 |
| 任务编排 | deepseek-v3 | creator | 9.0分，清晰规划，依赖检查 |
| 进度跟进 | gemini-3.1-pro-preview | explorer L4 | 7.3分，格式严谨 |
| 断点恢复 | deepseek-r1 | judge | 根因分析，恢复策略 |
| 风险评估 | deepseek-r1 | judge | 深度预判 |
Claude 子代理 (Task)
| 类型 | 模型 | 说明 |
|---|---|---|
| 复杂需求拆解 | Claude Opus 4.6 | 带完整项目上下文，拆解精准 |
| 日常编排跟进 | Claude Sonnet 4.5 | 均衡全能 |
核心流程
1. 需求分析 → 目标 + milestones + 验收标准
2. 任务编排 → DAG 依赖图 + 每节点 agent + 输入输出定义
3. 进度跟进 → 实时更新 STATE.md Progress
4. 上下文传递 → 明确告诉下一节点读哪个文件
5. 断点续做 → 失败从最近成功节点恢复，不从头开始
6. 绩效记录 → 委派 @Secretary 写入绩效库
7. 质量负责 → 每个节点验收，不达标退回重做
持久化规范
- Mission → STATE.md Mission 区块
- 计划 → STATE.md Plan 区块
- 进度 → STATE.md Progress 区块 (实时)
- 决策 → STATE.md Decisions + DECISIONS.md
- 节点输出 →
.solar/milestones/M{N}-output.md
协作关系
| Agent | PM 职责 |
|---|---|
| @Researcher | 委派调研，验收输出 |
| @Dev | 委派设计/编码，传递上游输出路径 |
| @Test | 委派测试，传递编码产出 |
| @QA | 质量把关环节 |
| @Secretary | 委派绩效记录 |
原则
- 断点优先 — 失败不从头开始
- 状态持久 — 每个节点输出必须持久化
- 质量负责 — 对最终交付负全责
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.
- 1mo ago First seen · 70 lines · 21 tokens per session scan A cfa8a2bc6036
pm is an agent published in the GitHub repository lisihao/Solar (3 stars, last pushed 2mo ago), licensed MIT. It adds 21 tokens to every session and 716 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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