Agent skill · Business & Finance

diagnostics-intake

Fast founder-input capture for the Diffmode growth-tactics pipeline (the diagnostics stage). Produces WS/01-diagnostics/founder-input.md in the exact schema the enrichment + synthesis stages read. Two modes — (A) URL mode researches a product's website (homepage/pricing/about) plus a web-research pass to prefill the researchable fields, then marks founder-only gaps for confirmation; (B) Q&A mode formats a minimal (~2-minute) answer set into the schema. Use as the entry point of start, or whenever a workspace needs a founder-input.md before enrichment.

acogood152★ · 1 repos on radarProfile →
claude-codecodexApache-2.0
Install
npx skills add acogood/diffmode_free --skill diagnostics-intake --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 11 KB
Bundled scripts: none
Version: 1.0.0
Path: plugin/skills/diagnostics-intake/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 153 · +1 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Diagnostics — Intake (fast founder-input) You produce a single file: `WS/01-diagnostics/founder-input.md`, in the **exact schema** the rest of the pipeline reads (enrichment, the constraints generator's field parser, and synthesis all key off these sections and labels). This replaces the slow 20-minute diagnostic interview with a ~2-minute path: research what's public, ask only what isn't. This is **capture, not analysis** — no strategy, no recommendations, no channel picks. That separation is load-bearing: later stages depend on raw, un-editorialized founder context. ## Inputs & Output The invoker provides (do not hardcode absolute paths): - **MODE A — `url`** (a website, e.g. `https://theona.ai`): research the site + company. - **MODE B — `answers`**: a block of founder answers to the minimal question set below (the orchestrator collects these in the main thread; you format them). - **MODE A+B**: both — research the URL AND fold in any founder answers the brief passed (answers always win over researched guesses). - **OUTPUT**: write to `WS/01-diagnostics/founder-input.md` (path supplied by invoker). If neither `url` nor `answers` is present, write the schema with every must-ask

What's inside
Steps it walks through
  1. Inputs & Output
  2. Field provenance (what to research vs what to ask)
  3. Minimal question set (Q&A mode — target ≤ 2 minutes)
  4. Procedure
  5. Mode A — URL research → prefill
  6. Mode B — Q&A → format
  7. Both modes — derive Module Routing (Section 7) mechanically
  8. Output template (write EXACTLY this structure)
  9. Validation checklist (self-check before returning)
More from diffmode_free
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About this skill
What does the diagnostics-intake skill do?

Fast founder-input capture for the Diffmode growth-tactics pipeline (the diagnostics stage). Produces WS/01-diagnostics/founder-input.md in the exact schema the enrichment + synthesis stages read. Two modes — (A) URL mode researches a product's website (homepage/pricing/about) plus a web-research pass to prefill the researchable fields, then marks founder-only gaps for confirmation; (B) Q&A mode formats a minimal (~2-minute) answer set into the schema. Use as the entry point of start, or whenever a workspace needs a founder-input.md before enrichment.

How do I install it?

Run `npx skills add acogood/diffmode_free --skill diagnostics-intake --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From acogood/diffmode_free, a repository with 153 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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