fit-scorer Checked

rved from discovery/registry or generated once for this lineage; raw identity locators remain transient.

• The typed goal/context and the Suitability item states are preserved for the gate; Unknown prevents a Suitability read.
• Any commercial-fit ranking is visibly separate from the Suitability read and cannot override a veto or missing evidence.
• If a Retro Card is supplied, its next_campaign_hypothesis is visible only as a falsifiable test constraint/commercial-matrix context; its evidence_refs are pointers for fresh investigation, not STAR item evidence or an automatic selection rule.
• **Primary next skill**: campaign-planner (../../target/campaign-planner/SKILL.md) — turn the ranked shortlist into an approved campaign plan. If that plan is already approved and outreach-ready, hand off to outreach-manager (../../activate/outreach-manager/SKILL.md) instead; competitor benchmarking is optional.

### Handoff Summary

> Emit the standard shape from skill-contract.md §Handoff Summary Format (../../../references/skill-contract.md).

Data Sources

This family needs no live integrations (Tier 1). Fit Scorer works end to end by asking the user for the inputs it scores — transient handles or profile locators, audience targets, brand values, and any metrics they have. A connector sharpens the numbers but none is required.

• ~~influencer database — follower counts, audience demographics, and partnership history.
• ~~social platform analytics — engagement rate, comment quality samples, posting cadence, growth trend.
• ~~audience intelligence — real-vs-bot follower estimates and audience overlap with your target.
• **Roster record (keyless Tier 1)** — prior contact, response reputation, and delivery history come from memory/creators/<aggregate-id>.md when the creator is rostered (creator-registry (../../../protocol/creator-registry/SKILL.md) curates it); ~~CRM is an optional Tier-2 sharpener for the same history when no roster record exists.

**Measured YouTube inputs (free key)**: for YouTube candidates, python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/youtube.py" videos @handle --limit 10 supplies the engagement-authenticity inputs directly — per-video views/likes/comments against the displayed subscriber base (views-to-subs consistency, comment rate, cadence) — so those sub-scores come from **Measured** numbers instead of screenshots. Free YOUTUBE_API_KEY; shortlist vetting only (ToS refuses bulk-harvesting quota). See scripts/connectors/README.md (../../../scripts/connectors/README.md).

With zero integrations, ask the user to supply each value the scoring tables request; the framework and weighting still produce a defensible ranking. See CONNECTORS.md (../../../CONNECTORS.md) for the free/keyless recipe per category.

Instructions

The contract-compatible copied layouts live in references/scoring-templates.md (references/scoring-templates.md): use the creator_ref-only typed STAR-S1–STAR-S10 evidence table for the Suitability read, then the optional commercial_fit_score tables for separate decision support. Never copy a raw locator into those outputs.

1. **Lock identity and typed context.** Reuse the opaque creator_ref explicitly carried by discovery, or a creator-registry aggregate ID only when its handle link is verified. If the user supplies only a raw handle/profile URL and no verified aggregate exists, generate one random creator-<UUIDv4> and reuse it unchanged across this report, any authorized save, and downstream handoffs. Never set creator_ref to a raw handle, name, URL, email, provider ID, or deterministic hash of one; keep those locators transient for evidence acquisition. Resolve an opaque ref only through its accompanying authorized artifact or verified registry link. If neither is available, request the transient locator and preserve the identity as unresolved rather than guessing or merging. Then require the creator target and target version, named STAR profile/goal (awareness|engagement|conversion|brand-building), assessment_time: forecast|actual, shared campaign rollup_id, observation date, platform/tier/niche cohort, evidence window, material context object, and current STAR catalog_version — the exact typed identity the gate will reuse. If any field is absent, do not invent it: return NEEDS_INPUT, name the missing fields, and preserve the supplied identity unchanged for resume. When a Campaign Retro Card is supplied, record its evidence_refs and next_campaign_hypothesis in a separate non-scoring prior-cycle context block; neither becomes part of the STAR typed identity.

2. **Freeze evidence for the current window.** Use current creator analytics, public observations, roster history, and cohort benchmarks with source/date/type/confidence. A Retro Card and its evidence_refs are discovery pointers only, never STAR item evidence. If a referenced primary source is independently reacquired and qualifies in the current evidence window, cite that fresh observation rather than the card. Missing or refused private access is Unknown, never Fail or Partial.

3. **Score Suitability only.** Evaluate the Suitability items S1–S10 (audience composition/realness, follower-growth integrity, reach reliability, engagement health and authenticity, credibility, and deal-independent brand/category fit) from star-benchmark.md (../../../references/star-benchmark.md)