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/lisihao/solar/retronpx skills add lisihao/Solar --skill retrogit 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/skills/lisihao/solar/retro)<a href="https://agentmods.dev/skills/lisihao/solar/retro"><img src="https://agentmods.dev/badge/skills/lisihao/solar/retro.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 | $0.00015 | $0.00323 |
| Opus 5 | $0.00008 | $0.00161 |
| Sonnet 5 | $0.00003 | $0.00065 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
retro 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 yesterday.
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
Skill: retro
Post-sprint retrospective: what worked, what failed, lessons extracted, STATE.md updated.
Trigger
User says: 回顾, 复盘, retro, /retro
Steps
- Read eval.md — review all PASS/FAIL items from the sprint evaluator
- What worked — list 2-3 things that went well
- What failed — list FAIL items with root-cause (not symptoms)
- Lessons — actionable rules extracted from failures
- Update STATE.md — add to Progress.Done + Next Actions if needed
- Write cortex — INSERT INTO cortex_sources for each lesson (credibility ≥ 0.8)
- Write sys_favorites — if insight score ≥ 7
Output format
## Worked
- ...
## Failed
- [item]: root-cause
## Lessons Extracted
1. [rule]: why it matters
## Cortex entries written: N
## STATE.md updated: yes/no
Done when
All FAIL items have root-causes, ≥1 cortex entry written, STATE.md updated.
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.
- yesterday First seen · 50 lines · 15 tokens per session scan A 80e2adf91c4c
retro is a skill published in the GitHub repository lisihao/Solar (2 stars, last pushed 22d ago), licensed MIT. It adds 15 tokens to every session and 323 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.
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discuss
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pull
Distill large context files (evaluation artifacts, schema dumps, query result sets, analysis outputs) into LLM-optimized dense form or human-readable narrative (--human). Default output is machine-dense; --human produces a prose summary for stakeholder consumption.