fit-scorer
Rank Influencers for Campaign Fit
Creator shortlists are difficult to compare consistently across audience, credibility, engagement, and campaign needs. This skill applies typed ACE scoring and separates commercial fit.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "fit-scorer" from https://skillstore.io/skills/aaron-he-zhu-fit-scorer.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-fit-scorer/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "fit-scorer". Compare three sustainable fashion creators for a conversion campaign.
Expected outcome:
- Creator A leads commercial fit because audience overlap and availability are strongest.
- Creator B has an ACE veto from verified inauthentic engagement.
- Creator C remains provisional because audience authenticity is Unknown.
Using "fit-scorer". Score one YouTube creator with incomplete audience data.
Expected outcome:
- ACE coverage is incomplete, so no final total is issued.
- Available engagement evidence is dated and labeled Measured.
- The report requests audience authenticity data before outreach.
Security Audit
SafeMost findings are scanner false positives caused by Markdown code fences, inline code, and relative documentation links. The skill explicitly runs local Python tooling, uses shell command substitution, and expects a YouTube API key. No prompt injection or data-exfiltration intent was found in the reviewed files.
Capability review items (4)
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
Risk Factors
📁 Filesystem access (22)
⚙️ External commands (19)
🌐 Network access (2)
🔑 Env variables (1)
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https://skillstore.io/skills/aaron-he-zhu-fit-scorer/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<iframe src="https://skillstore.io/embed/skills/aaron-he-zhu-fit-scorer.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
aaron-he-zhu. (2026). fit-scorer security audit report (audit version 7) [Author version 17.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-fit-scorer/audits/7BibTeX citation
@techreport{aaron-he-zhu-aaron-he-zhu-fit-scorer-2026,
author = {aaron-he-zhu},
title = {fit-scorer security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/aaron-he-zhu-fit-scorer/audits/7},
note = {Author version 17.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "fit-scorer security audit report (audit version 7)"
version: "17.0.0"
type: report
authors:
- name: "aaron-he-zhu"
date-released: "2026-07-12"
url: "https://skillstore.io/skills/aaron-he-zhu-fit-scorer/audits/7"
identifiers:
- type: other
value: "skillstore:aaron-he-zhu-fit-scorer:audit:7"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
Prioritize a Campaign Shortlist
Compare shortlisted creators under one campaign goal and identify evidence-backed outreach priorities.
Standardize Client Recommendations
Apply one typed rubric across creators while keeping client-specific commercial fit separate.
Audit Creator Evidence
Review credibility vetoes, missing metrics, and confidence before approving a partnership.
Try These Prompts
Score @[handle] for [campaign]. Use goal [goal] and list the evidence needed before making a recommendation.
Compare @[handle1], @[handle2], and @[handle3] for [campaign]. Show ACE results separately from commercial fit.
Audit these creator metrics for [campaign]. Mark missing data Unknown, identify critical controls, and explain what prevents a final score.
Rank [creators] for [campaign] using [goal]. Include typed context, dated evidence, veto checks, commercial terms, confidence, and rerun conditions.
Best Practices
- Use the same evidence window, cohort, and campaign goal for every compared creator.
- Keep ACE results separate from campaign-specific commercial-fit scores.
- Verify critical failures and refresh stale metrics before approving outreach.
Avoid
- Do not treat missing or refused private data as a failure.
- Do not hand-calculate an ACE total when the deterministic scorer is unavailable.
- Do not let commercial fit override an ACE veto or unresolved evidence gap.
Frequently Asked Questions
Does this skill find influencers?
What is the ACE rubric?
Can it score creators without integrations?
Does brand fit change the ACE score?
Can it compare creators across platforms?
Does it save reports automatically?
Developer Details
Author
aaron-he-zhuLicense
Apache-2.0
Author version
v17.0.0
Skillstore revision
r1
Repository
https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/influencer/discover/fit-scorerRef
d71c7417a35d5c2624161bd2fe8de8a41a362128
Maintenance freshness
7/18/2026
Usage
1 downloads · 1 views
File structure