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influencer-discovery

Use when the user asks to "find influencers", "build an influencer list", or "discover creators in [niche]"; produces a multi-platform candidate pool, per-influencer evidence profiles, authenticity red-flag screening, and a Fit-readiness queue without action ranking. Not for STAR scoring or ranking a known shortlist — use fit-scorer. 达人挖掘/找达人/创作者名单

66

Quality

82%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a well-structured, action-oriented overview with strong workflow checkpoints and clean progressive disclosure into reference files. The main weakness is redundancy in the identity-ref and authorization language repeated across the contract and step sections.

Suggestions

Consolidate the opaque creator_ref / identity_status / authorization rules so they are stated once in the Skill Contract and merely referenced from Steps 2 and 4, reducing token cost.

Add the full registry-events.py 'operation: propose' invocation example so the roster-write step is fully copy-paste ready.

Tighten the repeated freshness/evidence_window explanation (currently restated in Step 4 and the closing paragraph) into a single canonical statement.

DimensionReasoningScore

Conciseness

Mostly efficient and free of basic-concept padding, but the opaque-identity-ref and authorization language recurs across the Skill Contract, Step 2, and Step 4 and could be tightened by consolidating.

3 / 5

Actionability

Provides concrete executable commands (youtube.py invocations, oEmbed URLs), specific evidence labels, save paths, and per-step template blocks, with only minor gaps such as the full registry-events.py invocation form.

4 / 5

Workflow Clarity

Six clearly sequenced steps each map to a template, with explicit NEEDS_INPUT/PARTIAL/READY_FOR_FIT checkpoints and refresh_required feedback loops for this batch/authorized-write operation.

5 / 5

Progressive Disclosure

The body is an overview pointing to verified one-level-deep references (templates.md, platform-vetting.md, creator-dossier.md) with each step signaling its template block; content is appropriately split and easy to navigate.

5 / 5

Total

17

/

20

Passed

Description

87%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it pairs concrete capability outputs with explicit 'Use when...' trigger phrases and a clear negative boundary against the sibling fit-scorer skill. Minor room to expand trigger-term synonyms and fully enumerate the discovery actions.

DimensionReasoningScore

Specificity

Lists several concrete outputs ('multi-platform candidate pool, per-influencer evidence profiles, authenticity red-flag screening, and a Fit-readiness queue') with only minor coverage gaps; not quite comprehensive enough for a 5.

4 / 5

Completeness

Explicitly answers both what (produces candidate pool, evidence profiles, red-flag screening, Fit-readiness queue) and when (explicit 'Use when...' clause with concrete trigger phrases), matching the top anchor.

5 / 5

Trigger Term Quality

Includes natural phrases users would say ('find influencers', 'build an influencer list', 'discover creators in [niche]') plus Chinese synonyms, but a few natural variations are missing.

4 / 5

Distinctiveness Conflict Risk

Has a clear scout-phase niche with distinct discovery triggers and an explicit negative boundary ('Not for STAR scoring or ranking a known shortlist — use fit-scorer'), minimizing conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

75%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation12 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

relative_links

Relative link issues: 23 suspicious

Warning

referenced_paths_exist

Referenced path issues: 2 missing, 1 deeper-than-1-level

Warning

Total

12

/

16

Passed

Repository
aaron-he-zhu/aaron-marketing-skills
Reviewed

Table of Contents

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