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/init-linearnpx skills add cliffren/swf --skill init-lineargit 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 | $0.00025 | $0.00849 |
| Opus 5 | $0.00013 | $0.00425 |
| Sonnet 5 | $0.00005 | $0.00170 |
| Haiku 4.5 | $0.00003 | $0.00085 |
Grade A, and why
init-linear 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Initialize Linear Workspace
One-time setup to prepare Linear workspace for the SWF workflow.
Workflow
-
Check current state:
- List existing teams, projects, labels
- Report what's already set up vs what's missing
- Skip anything that already exists
-
Create Label groups and labels:
type(任务类型) ├── dev #4EA7FC 编码开发 ├── experiment #F2C94C 实验运行 ├── writing #6FCF97 文档/论文写作 ├── figures #BB87FC 图表制作 └── admin #BDBDBD 提交/沟通/杂务 executor(执行者) ├── agent:claude #D2915D Claude Code 处理 ├── agent:codex #26B5CE Codex 处理 └── manual #EB5757 需要手动操作- First create parent groups with
create_issue_labelusingisGroup: true:type(isGroup: true)executor(isGroup: true)
- Then create sub-labels with
parentparameter pointing to the group name:- e.g.,
create_issue_label(name: "dev", color: "#4EA7FC", description: "编码开发", parent: "type")
- e.g.,
- Skip any that already exist
- First create parent groups with
-
Create Ideas project:
- Name: Ideas
- Icon: :bulb:
- Description: "立项评估漏斗。每个想法作为一个 issue,评估任务作为 sub-issue。评估通过 → 归档 issue,建独立 Project 和 GitHub repo。评估否决 → 归档 issue,留记录。"
- Skip if already exists
-
Create Archive project:
- Name: Archive
- Icon: :file_cabinet:
- Description: "归档中心。所有项目的 Done/Canceled issues 导出为 Documents 存放于此。用于释放 250 issue 额度。"
- Skip if already exists
-
Clean up default issues (if present):
- Check for Linear onboarding issues (titles like "Get familiar with Linear", "Set up your teams", etc.)
- Ask user: "发现 X 个 Linear 默认引导 issue,要标记为 Canceled 吗?"
- If yes, mark them Canceled
-
Remind team settings:
请在 Linear 网页上手动配置以下设置: Settings → Team Settings → Workflows & automations: - Auto-close parent issue: 开启(子 issue 全完成时自动关闭父 issue) - Auto-archive closed items after: 1 month(最短选项) 完成后 SWF 工作流即可使用。 -
Report:
## Linear 初始化完成 ✓ Labels: type (5) + executor (3) ✓ Ideas 项目 ✓ Archive 项目 ○ 默认 issue 已清理 手动设置提醒: - [ ] Auto-close parent issue - [ ] Auto-archive = 1 month 下一步: - /swf:idea <name> 记录第一个研究想法 - /swf:import 导入已有项目
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 · 92 lines · 25 tokens per session scan A 72e9d03e93fa
init-linear is a skill published in the GitHub repository cliffren/swf (5 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 849 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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