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 commands/tdwhere123/do-it/do-it-retrospectivegit clone --depth 1 https://github.com/tdwhere123/do-itWrote 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/commands/tdwhere123/do-it/do-it-retrospective)<a href="https://agentmods.dev/commands/tdwhere123/do-it/do-it-retrospective"><img src="https://agentmods.dev/badge/commands/tdwhere123/do-it/do-it-retrospective.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 | $0.00042 | $0.00369 |
| Opus 5 | $0.00021 | $0.00185 |
| Sonnet 5 | $0.00008 | $0.00074 |
| Haiku 4.5 | $0.00004 | $0.00037 |
Grade A, and why
do-it-retrospective 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 today.
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
/do-it-retrospective
/do-it-retrospective on 开启当前项目的本地、去敏学习事件记录;off 立即停止新增记录;status 只报告当前状态;report 输出本地复盘报告。记录默认关闭。新事件写在 .do-it/runtime/events/learning.jsonl,兼容副本仍在 .do-it/runtime/retrospective/,不会进入 Git。
当参数为 on、off 或 status 时,只确认状态并停止;不要改代码、规则文件、adaptive profile、Core 或历史记录。无参数时显示这份用法,不自动展示报告。
report 时,读取本地事件并做复盘,先判断原因(code/test、project truth、task contract、host gap、adaptive candidate),再给出不超过三条候选经验。单次事件默认 no-action。不要把观察当成已激活策略,也不要自动写入 .do-it/runtime/adaptive/profile.md 或 do-it-core。若要改已有 AGENTS.md / CLAUDE.md,先给出目标文件和精确措辞,等待用户确认。不要自动创建规则文件、提交或推送。
此 slash command 是 Claude Code 的发现入口。其它宿主只有在原始文本实际到达 prompt hook 时才支持同样的精确文本;否则用 do-it-retrospective skill 或明确自然语言请求。
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.
- today Changed · +9 tokens per session 252c68110bf7
- 5d ago First seen · 14 lines · 33 tokens per session scan A df6b8cd71c66
do-it-retrospective is a command published in the GitHub repository tdwhere123/do-it (27 stars, last pushed 3d ago), licensed MIT. It adds 42 tokens to every session and 369 once invoked, about $0.0002 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 commands, from other repositories
forked
You are in a forked session - a conversation branched from a main working session to explore an issue, discuss options, or make decisions without polluting the main context window.
status
Check status of Kimi plugin jobs.
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.