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/cliffren/swf/donenpx skills add cliffren/swf --skill donegit clone --depth 1 https://github.com/cliffren/swfWhat 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 | $0.00024 | $0.00401 |
| Opus 5 | $0.00012 | $0.00200 |
| Sonnet 5 | $0.00005 | $0.00080 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
done 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 2d 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
Finish Current Task
Complete a task by documenting what was done and updating Linear.
Input
$ARGUMENTS — optional issue ID (e.g., TAO-5). If omitted, look for the In Progress issue in the current project.
Workflow
-
Identify the task:
- If issue ID provided, fetch it
- Otherwise, find the In Progress issue assigned to "me" in the current project
- If multiple In Progress issues exist, list them and ask which one
-
Generate summary:
- Review what changed:
git diff main...HEAD --stator recent commits since task started - Summarize the changes in a concise comment:
## 完成摘要 - 做了什么(1-3 bullet points) - 关键文件变更 - 测试状态 ## 备注 - 发现的后续问题(如果有)
- Review what changed:
-
Confirm with user:
- Show the draft comment
- Ask: "确认标记为 Done 吗?"
-
Update Linear:
- Post the summary as a comment on the issue
- Mark the issue as Done
-
Suggest next steps:
- Check remaining Todo issues in the project
- If there are more: "还有 N 个 Todo issue,要继续吗?(
/swf:next)" - If none: "当前 milestone 的任务都完成了,要规划下一批吗?(
/swf:plan-next)" - If ADR-worthy decisions were made: "这个任务涉及架构决策,要记录 ADR 吗?(
/swf:adr)"
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.
- 2d ago First seen · 49 lines · 24 tokens per session scan A 48b29b6331b2
done is a skill published in the GitHub repository cliffren/swf (5 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 401 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 2026-08-31.
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auto-perf-optimize
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chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
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cpu-profile-analysis
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