Fit Scorer

Score each shortlisted creator on the typed STAR Suitability (S) dimension, then keep campaign-specific commercial fit in a separate prioritization matrix. The Suitability read is portable and brand-independent; the commercial matrix is not a Suitability score and never enters the SQS.

Quick Start

Score one influencer:

Score @[handle] for [brand/campaign] and tell me if they're a good fit

Compare and rank a shortlist:

Compare and rank these influencers for [campaign]: @influencer1, @influencer2, @influencer3

Skill Contract

Reads: brand/campaign context, target audience definition, campaign goal, and a shortlist of influencer handles (supplied by the user or carried over from
```
influencer-discovery
```
). Optional prior audience profiles from
```
memory/influencer/audience-mapper/
```
and competitor partner benchmarks from
```
memory/influencer/competitor-tracker/
```
. For rostered creators, read partnership history and audience-stat provenance from
```
memory/creators/<handle-slug>.md
```
— the creator-registry roster record — as Partnership Potential inputs.
Writes: only with explicit authorization, a report containing the typed Suitability (S) read plus a separately labeled commercial-fit comparison at
```
memory/influencer/fit-scorer/YYYY-MM-DD-<topic>.md
```
.
Promotes: only with separate authorization, evidence-backed top picks and their exact Suitability (S) read and catalog version; never promote an unscored or provisional result.
Done when:
- Every creator has all 10 Suitability items
```
S1
```
  –
```
S10
```
  explicitly Pass/Partial/Fail/Unknown/N/A with dated evidence or a gap reason.
- 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.
Primary next skill: competitor-tracker — benchmark your top-scored picks against the creators competitors already partner with.

Handoff Summary

Emit the standard shape from skill-contract.md §Handoff Summary Format.

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 — handles, 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/<handle-slug>.md
```
when the creator is rostered (creator-registry 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.

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 for the free/keyless recipe per category.

Instructions

The commercial comparison layouts live in references/scoring-templates.md. They are optional decision support, not the STAR Suitability rubric.

Lock typed context. 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.
Freeze evidence. Use creator analytics, public observations, roster history, and cohort benchmarks with source/date/type/confidence. Missing or refused private access is Unknown, never Fail or Partial.
Score Suitability only. Evaluate the Suitability items
```
S1
```
–
```
S10
```
(audience composition/realness, follower-growth integrity, reach reliability, engagement health and authenticity, credibility, and portable brand/category fit) from star-benchmark.md. Campaign-specific commercial terms and availability stay in the separate matrix; cost and measured campaign conversion belong to Return (R), scored later by the gate.
Qualify critical-control evidence for handoff.
```
STAR-S2
```
covers demonstrated follower fraud / real-follower rate below the matching tier × platform × niche benchmark;
```
STAR-S6
```
covers demonstrated bought, coordinated, or pod-based engagement. Brand safety is the gate's Trust control
```
STAR-T3
```
, not a Suitability item. Mark an item Fail only from qualifying evidence, label it a potential gate finding, and operationally hold outreach while it stands. Do not call it a verified veto or apply the SQS cap/business verdict here; the auditor owns those decisions when it rolls up the full STAR run.
Record the Suitability read for the gate. Capture the
```
S1
```
–
```
S10
```
states with source/date/type/confidence as the portable Suitability (S) read. The creator-content-auditor gate folds this read into the full STAR run and runs the deterministic scorer for the profile-weighted SQS — this skill does not run the scorer or emit the SQS. Unknown means applicable evidence is missing and prevents a Suitability read; never soften Unknown to Partial or hand-calculate a composite.
Build the separate commercial matrix when requested. Use audience-to-campaign fit, content style, campaign-specific brand/category fit, commercial terms, availability, and partnership potential. Label its 1-5 total
```
commercial_fit_score
```
; it is not a Suitability score, cannot clear a Suitability veto, and never enters the SQS.
Rank transparently. Show the Suitability (S) read (or coverage/interval), critical controls, commercial fit separately, evidence confidence, and an outreach recommendation with owner/rerun condition. Do not rank an Unknown-heavy candidate as definitively superior.
Persist only with permission. Save the report only after authorization; request separate authorization before any hot-cache promotion or creator-registry proposal.

Compact Example

User: "Compare @ecofashionista, @greenwardrobe, @sustainablesarah for our sustainable fashion brand (goal: conversion)."

Output: Each creator receives

S1

–

S10

item states under the same campaign

rollup_id

; a Suitability (S) read exists only at complete applicable coverage, while the separate commercial matrix explains campaign-specific terms and availability. A verified below-benchmark real-follower rate marks

STAR-S2

Fail and holds outreach; refused access stays Unknown and prevents the read. Only creator-content-auditor may apply the later STAR business verdict/cap. Persistence is offered, not assumed.

Reference Materials

references/scoring-templates.md — all per-dimension tables, final-score rollup, comparison report, custom-weighting matrix, worked example, and tips.
skill-contract.md — shared contract and handoff summary format.
state-model.md — memory tiers and save-path conventions.
CONNECTORS.md — free/keyless data recipe per connector category.
Scoring rubric: star-benchmark.md — the STAR framework, the Suitability (S) dimension this skill reads (incl. the
```
STAR-S2
```
/
```
STAR-S6
```
veto items), and the profile-weighted SQS the gate computes.
Sibling skills: influencer-discovery, competitor-tracker, audience-mapper, outreach-manager.

Next Best Skill

Primary: competitor-tracker — benchmark your top-scored picks against the creators competitors already work with before you commit budget.

Alternates (same scout phase):

creator-content-auditor — when a complete Suitability read or potential
```
STAR-S2
```
/
```
STAR-S6
```
/
```
STAR-T3
```
control evidence is ready, stop and hand it to this sole STAR gate as a separate invocation; do not auto-run or simulate its verdict.
influencer-discovery — if the shortlist is too thin to rank, source more candidates.
audience-mapper — if audience-match scores are uncertain, tighten the target-audience definition first.

Termination note: Track a visited-set of skills invoked this session. If the recommended next skill has already run, stop and report the chain complete rather than re-invoking it. Stop after at most 3 hops (max-depth 3) and hand back to the user with the saved report path.

Related Skills

influencer-discovery - Find influencers to score
competitor-tracker - Benchmark against competitor partners
audience-mapper - Define target audience
outreach-manager - Contact top-scored influencers

fit-scorer

NPX Install

Tags

SKILL.md Content