# Fit > Rank what is worth building from a radar report — cross each complaint theme with verified-revenue proof (TrustMRR) and, when available, the developer's own persona card from devpersona (stack, strengths, risk patterns) to produce a founder–opportunity fit ranking with MVP scope and first-10-users source. Use when the user asks which idea to build, what would pay, "ne inşa etmeliyim", "hangisi para eder", "bana uygun fırsat", "rank these opportunities", or runs /painradar:fit. Requires a radar report from painradar:scan and runs it first if missing. Not for the complaint report itself — that is painradar:scan. Not for marketing — that is painradar:launch. - Skill: `hailneed/fit` (Agent Skill) - Install (CLI): `npx skillmds@latest add hailneed/fit` - Raw SKILL.md: https://api.skillmd.com/api/skills/hailneed/fit/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Marketing & Growth - Author: hailneed (https://skillmd.com/u/hailneed) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/hailneed/fit --- # Founder–opportunity fit Answer one question per theme: *is there pain, is anyone paying, and is this person the right one to build it?* Every score must point at evidence. No evidence, no ranking. **Language rule: write every user-facing output in the language the user is speaking with you.** ## Step 0 — Load inputs 1. Latest `~/.claude/radar/-.md` (+ `-raw.json`). If none or older than 14 days, run the `scan` skill of this plugin first. 2. **Persona (optional, local):** `~/.claude/persona/persona.md` written by devpersona. If present, read stack, strengths, risk patterns. If absent, say fit is estimated without a persona and suggest `/devpersona:analyze` — do not guess the user's skills. 3. **Money proof:** if `TRUSTMRR_API_KEY` is set, run `node "${CLAUDE_PLUGIN_ROOT}/scripts/radar.mjs" --topic "" --trustmrr "," --out "/.claude/radar/-money.json"` and use `trustmrr` median MRR / growth per category. Without a key, fall back to the public stats page (https://trustmrr.com/stats) and mark figures "(doğrulanmadı)" — never invent numbers. Map each theme to the closest TrustMRR category (Marketing, Developer Tools, Analytics, Security, Sales, Content Creation, …). ## Step 1 — Score (0–5 each, one line of evidence per score) | Dimension | What counts | |------------------|------------------------------------------------------------------------------------| | Pain | the theme's Signal from the radar report | | Money proof | verified startups earning in the adjacent category; median MRR; 30-day growth | | Competition gap | how many tools already serve it; is there a free/OSS incumbent or big vendor | | Founder fit | persona stack & strengths match the MVP; risk patterns that would hurt here | | Effort | 5 = MVP in ≤ 2 weeks solo, 1 = months or a team | | Platform risk | 5 = owns its data/channel, 1 = depends on one API/licence that may change | Fit = weighted: Pain 25 % · Money 20 % · Gap 20 % · Founder 15 % · Effort 10 % · Risk 10 %. State the weights in the report so the user can override them. ## Step 2 — Write `~/.claude/radar/-fit-.md` 1. Ranking table (theme, Fit 0–100, the six scores). 2. For the top 3: one-paragraph thesis · MVP scope (the *one* job it does, 3–5 bullets) · what to leave out · pricing hypothesis with comparable verified products (linked) · where the first 10 users are (specific communities/threads from the evidence) · the riskiest assumption and a ≤ 1-week test for it · evidence links. 3. "Do not build" notes: themes that are real pain but saturated (name the incumbents). 4. Persona notes: which persona traits helped or hurt each score (or "persona yok"). ## Step 3 — Reply Chat: the top 3 with Fit score and a one-line why; the single riskiest assumption of #1; then `/painradar:launch` for the go-to-market plan of the chosen one.