Borrowing it
Nothing to install: this file belongs to tt-11-dd/tether-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tt-11-dd/tether-ai/main/.agents/skills/plan-then-act/SKILL.mdgit clone --depth 1 https://github.com/tt-11-dd/tether-aiWrote 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/tt-11-dd/tether-ai/plan-then-act)<a href="https://agentmods.dev/skills/tt-11-dd/tether-ai/plan-then-act"><img src="https://agentmods.dev/badge/skills/tt-11-dd/tether-ai/plan-then-act/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/skills/tt-11-dd/tether-ai/plan-then-act"><img src="https://agentmods.dev/badge/skills/tt-11-dd/tether-ai/plan-then-act.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00047 | $0.00206 |
| Opus 5 | $0.00023 | $0.00103 |
| Sonnet 5 | $0.00009 | $0.00041 |
| Haiku 4.5 | $0.00005 | $0.00021 |
Grade A, and why
plan-then-act 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 9d 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
先计划再动手
短任务用本技能。若用户要「跨会话」或仓库已有 .agents/features.json，改走 continue-long-run；还没有清单则走 init-long-run。
- 只读：读 README、相关源码、
AGENTS.md/CLAUDE.md。不要 write / edit / patch。 - 把 3～7 条步骤写成 checklist（
- [ ]）。 - 停下来等用户确认，或当前权限是
plan时保持只读。 - 获准后按条目改文件，完成一项就把
- [ ]改成- [x]。
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.
- 9d ago First seen · 14 lines · 47 tokens per session scan A 01ff7b9951cd
plan-then-act is a skill published in the GitHub repository tt-11-dd/tether-ai (82 stars, last pushed yesterday), licensed MIT. It adds 47 tokens to every session and 206 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.
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