ideate

An idea-validation guide that turns a rough product idea, or a problem area, into a specific claim that can be tested with research.

In plain words
What is it for?
Use it to sharpen a product pitch, decide what to investigate, or find real user problems worth building for.
Why use it?
It removes the vagueness that makes it hard to tell whether an idea solves a real problem. It also prepares a research brief for checking demand.

Skill for Claude CodeCodex

Part of the metalworks plugin — 22 skills, 1 hook, 1 MCP server 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/lab2a/metalworks/ideate
Any agent
npx skills add Lab2A/metalworks --skill ideate
Clone the repo
git clone --depth 1 https://github.com/Lab2A/metalworks

Made for: Claude Code, Codex.

Or install metalworks, the plugin that ships this one along with the rest of its 22 skills, 1 hook, 1 MCP server.

Per session 132 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 990 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 $0.00132 $0.00990
Opus 5 $0.00066 $0.00495
Sonnet 5 $0.00026 $0.00198
Haiku 4.5 $0.00013 $0.00099

Measured 3d ago against content hash 66ea96b0a9a4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

ideate 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 3d 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.

plugin/skills/ideate/SKILL.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Preamble (run first)

Before any other tool, run the preflight MCP tool (or metalworks preflight on the CLI). If it reports setup issues or that an update is available, surface that to the user in one line and help them resolve it (install the missing extra/key, or pip install -U metalworks) before continuing. Skip only if the user has already passed preflight this session.

Read the reference; never reverse-engineer the source. The moment you need to know how metalworks behaves — provider/model resolution, which source/reader runs, config precedence, an error you hit, or the async run loop — STOP and read docs/operating-metalworks.md (bundled with this plugin) before opening any file under src/. It is the source of truth; do not derive behavior from source. (Full docs: https://metalworks.lab2a.ai/docs.) For a long-running run, poll status with the Monitor tool or a bounded loop — never a blind sleep.

You are at the front of the validate loop: turn a fuzzy starting point into one sharp, testable idea. You have two doors, and you pick based on what the user brings — a pitch, or a space to explore. Be a sharp, honest design partner: push for specificity, but do not invent demand evidence here (that's what demand + landscape measure next).

Pick the entry point

  • Idea-first — the user has an idea ("I want to build X", "is X worth it?"). Sharpen it.
  • Evidence-first — the user has a space, not an idea ("what should I build for Y?", "show me real pain in Z"). Surface the forks from a demand report and let them choose.

If the user has a report already and isn't sure, prefer evidence-first — grounded beats guessed.

Steps — idea-first

  1. Call ideate_from_idea with the raw idea (CLI: metalworks research ideate "<idea>"). It returns an IdeaSketch: a sharpened hypothesis, the pain it addresses, who it's for, and a brief ready to run demand on.
  2. Reflect it back and push once: is the hypothesis specific enough to be falsifiable? Is the pain a real pain or a feature wish? Refine the idea text and re-run if it's still vague.
  3. End on the next action: "run demand on this brief, then landscape, then assess." The sketch is a hypothesis — say so plainly; it carries no evidence yet.

Read the full file on GitHub · 63 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. 3d ago First seen · 63 lines · 0 tokens per session scan A 66ea96b0a9a4

Subscribe to this mod's changes

ideate is a skill published in the GitHub repository Lab2A/metalworks (6 stars, last pushed 2mo ago), licensed MIT. It adds 132 tokens to every session and 990 once invoked, about $0.0007 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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