idea

A research-idea workflow that creates a Linear issue and standard follow-up tasks for evaluating it. It first asks questions to clarify the idea and saves a written summary.

In plain words
What is it for?
Use it to record a new research idea, discuss its problem and contribution, review related work, assess feasibility, choose technology, draft a design, and plan a framework diagram.
Why use it?
It removes the need to set up the same research-planning tasks by hand and helps turn an early idea into a clearer proposal.

Skill for Claude CodeCodex

Part of the swf plugin — 16 skills, 1 agent shipped together

Install

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.

agentmods
npx agentmods add skills/cliffren/swf/idea
Any agent
npx skills add cliffren/swf --skill idea
Clone the repo
git clone --depth 1 https://github.com/cliffren/swf

Made for: Claude Code, Codex.

Or install swf, the plugin that ships this one along with the rest of its 16 skills, 1 agent.

Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,717 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00017 $0.01717
Opus 5 $0.00009 $0.00859
Sonnet 5 $0.00003 $0.00343
Haiku 4.5 $0.00002 $0.00172

Measured 2d ago against content hash d3f75b164952, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

idea 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.

skills/idea/SKILL.md · 155 lines

How it starts

The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.

New Research Idea

Create a new research idea in the Linear Ideas project and set up standard evaluation sub-issues.

Input

$ARGUMENTS — the name/title of the research idea. If not provided, ask the user.

Workflow

  1. Create the main issue in the Ideas project:

    • Title: $ARGUMENTS
    • Status: Todo
    • Ask the user for a 1-2 sentence description of the idea
  2. Discuss and clarify the idea with the user before creating sub-issues:

    • Ask one question at a time:
      • "这个想法要解决什么问题?"
      • "和现有方法/工具的区别是什么?"
      • "大致的技术思路是什么?"
      • "预期的贡献是什么?(方法创新?性能提升?新应用?)"
    • Summarize the discussion into a clear idea statement
    • Save to ~/Projects/ideas/<idea-slug>/idea-statement.md
    • Update the main issue description with the idea statement
  3. Create evaluation sub-issues under the main issue:

    Sub-issue Labels Output template
    文献调研:领域进展、找到 gap writing, agent:claude see below
    评估意义/创新性/可行性 writing, agent:claude copy key insights into literature-review.md, keep feasibility.md as-is
    技术选型 writing, agent:claude
    撰写 design.md 初稿 writing, agent:claude
    画框架图初版 figures, agent:claude
  4. Create local workspace:

    • Create directory: ~/Projects/ideas/<idea-slug>/
    • This is NOT a git repo, just a local workspace for evaluation drafts
    • Evaluation outputs go here as markdown files:
      ~/Projects/ideas/<idea-slug>/
      ├── idea-statement.md        ← 想法讨论梳理
      ├── literature-review.md     ← 文献调研
      ├── feasibility.md           ← 可行性评估
      ├── tech-selection.md        ← 技术选型
      ├── design.md                ← design.md 初稿
      └── framework.svg            ← 框架图
      
    • After each sub-issue is done, post a brief summary (3-5 sentences) as a Linear issue comment, with detailed content in the local file
    • When /swf:promote runs, it migrates design.md and framework.svg into the new repo
  5. Set up evaluation order:

    • The sub-issues have dependencies:
      ① 文献调研 → ② 评估可行性 → ③ 技术选型 → ④ design.md 初稿
      ⑤ 框架图(独立,不阻塞,Backlog)
      
    • Note: idea discussion (step 2) happens BEFORE sub-issues are created, so it's not a sub-issue
    • ①~④ set to Todo, with blocking relations: ② blocked by ①, ③ blocked by ②, ④ blocked by ③
    • ⑤ 框架图 set to Backlog — optional during evaluation, can be done if time permits or deferred to after promote

Read the full file on GitHub · 155 lines

Changes

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.

  1. 2d ago First seen · 155 lines · 17 tokens per session scan A d3f75b164952

Subscribe to this mod's changes

idea is a skill published in the GitHub repository cliffren/swf (5 stars, last pushed 4mo ago), licensed MIT. It adds 17 tokens to every session and 1,717 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens

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.

microsoft/vscode · 51 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens