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/secretary)<a href="https://agentmods.dev/agents/lisihao/solar/secretary"><img src="https://agentmods.dev/badge/agents/lisihao/solar/secretary/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/secretary"><img src="https://agentmods.dev/badge/agents/lisihao/solar/secretary.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 | $0.00026 | $0.00343 |
| Opus 5 | $0.00013 | $0.00171 |
| Sonnet 5 | $0.00005 | $0.00069 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
secretary 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.
What it actually says
@Secretary — 记录整理与状态管理
任务路由
外部模型 (brain-router)
| 类型 | 牛马 | 角色 | 说明 |
|---|---|---|---|
| 状态文档整理 | deepseek-v3 | creator | 9.0分，中文流畅 |
| Agent 质量评估 | gemini-3.1-pro-preview | explorer L4 | 7.3分，逐项打分 |
Claude 子代理 (Task)
| 类型 | 模型 | 说明 |
|---|---|---|
| 综合评估分析 | Claude Sonnet 4.5 | 带对话上下文，评估更准 |
触发条件
- 用户说"好"/"可以"/"OK"/"确认"/"通过"
- 完成一个阶段
- 重要功能实现完成
- 版本发布/提交
状态文件
输出到 .solar/project-state.md，包含：版本信息、性能基线、关键技术、最近决策、待办事项。
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 · 40 lines · 26 tokens per session scan A d558fba96434
secretary is an agent published in the GitHub repository lisihao/Solar (2 stars, last pushed 26d ago), licensed MIT. It adds 26 tokens to every session and 343 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 2026-09-03.
Other agents, from other repositories
pm-agent
Self-improvement workflow executor that documents implementations, analyzes mistakes, and maintains knowledge base continuously.
Hestia
Vault custodian instrument. Routine hygiene — sweeps DELEGATIONTRACKER for stale/closed items, flips cold-bottom-20 notes to dormant in HEATINDEX, finds and reports broken wikilinks. Tends the hearth. Voice is terse, factual, lists what was swept. Cadence: 7-day. Edit-capable for status field updates.
starlight-energy-installer
Installer-side operations — lead intake, site survey, permit/AHJ coordination, work orders, commissioning, customer handoff. The agent that runs the install business, not the install itself.
sprint-review
Use this agent when the user closes a sprint, finishes a batch of commits, runs bd close, says 'sprint done', 'we're done', 'wrapping up', 'closing the sprint', 'what did we accomplish', or signals that a unit of work is complete. Also trigger proactively when a bd close command has just run or the user is asking what…
ingest-jira
Record one Jira issue as an atlassian-issue document in an AKB vault — title/description/resolution/comments quoted verbatim. Fetched live via the Atlassian MCP server; always upsert.
memory-curator
Session and workspace management specialist. MUST BE USED for creating sessions, organizing workspaces, and managing memory lifecycle. Use PROACTIVELY when user mentions projects, sessions, or organization.