| name | fit-scorer |
| slug | fit-scorer |
| displayName | Fit Scorer · 红人适配评分 |
| summary | 用 typed STAR 适配度(S) 维度评估创作者，并将活动商业适配度作为独立矩阵排序 |
| description | Use when the user asks to "score this influencer", "rank these creators for our campaign", or "tell me which influencer is the best fit"; produces the typed STAR Suitability (S) read plus a separately labeled campaign-fit ranking without mixing campaign-specific commercial fit into the Suitability read. Not for finding new influencers — use influencer-discovery; not for sending outreach — use outreach-manager. |
| version | 18.0.0 |
| license | Apache-2.0 |
| compatibility | Claude Code and compatible agent-skill hosts |
| homepage | https://github.com/aaron-he-zhu/aaron-marketing-skills |
| when_to_use | Use when a user has a shortlist of influencers and needs an objective, weighted score to prioritize outreach, choose between candidates, justify a selection to stakeholders, set consistent evaluation standards, compare creators across niches or platforms, or build long-term partner tiers. Activates on requests like score @handle for our brand, compare and rank these creators, or which of these is the best fit. |
| argument-hint | <brand or campaign> <influencer handle(s)> [campaign goal: awareness|engagement|conversion] |
| metadata | {"author":"aaron-he-zhu","version":"18.0.0","discipline":"influencer","phase":"scout","geo-relevance":"low","hermes":{"tags":["marketing","influencer","scout"],"category":"influencer"},"openclaw":{"emoji":"📣","homepage":"https://github.com/aaron-he-zhu/aaron-marketing-skills"}} |
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. Declare creator target/version, goal (
awareness|engagement|conversion|brand-building), assessment_time: forecast|actual, shared campaign rollup_id, observation date, platform/tier/niche cohort, and evidence window — the typed context the gate will score the full STAR run under.
- 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.
- Verify critical failures. The Suitability vetoes are
STAR-S2 (verified follower fraud / real-follower rate below the tier × platform × niche benchmark) and STAR-S6 (verified bought, coordinated, or pod-based engagement); brand-safety is now the gate's Trust veto STAR-T3, not a Suitability check. Flag any verified Suitability veto and operationally hold outreach while it stands; the SQS cap (min(raw,59) for one verified veto, BLOCK for two or more) is applied by the gate 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 a typed conversion Suitability (S) read using the same campaign rollup_id; the separate commercial matrix explains campaign-specific terms and availability. A verified real-follower rate below the tier benchmark fails STAR-S2; folded into the gate it caps a one-veto SQS at 59, while refused access stays Unknown and prevents a read. 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):
- 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.
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