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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

Quality

84%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

73%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.

A well-structured, highly actionable skill body with an exemplary six-step workflow — explicit stop conditions, freshness/refresh gating, and a done-when checklist — plus verifiable one-level-deep references. The main costs are token efficiency: run-on contract sentences and rules repeated across three sections, and some dense policy detail inlined where the bundle's reference files could hold it.

Suggestions

Consolidate the opaque creator_ref / identity-status rules into one place (e.g., a short 'Identity & Refs' section or a reference file) and have Steps 2, 4, and 5 point to it instead of restating them, cutting significant duplicated tokens.

Break the ~180-word 'Writes' bullet in the Skill Contract into 2–3 shorter bullets (save path & naming, opaque refs & identity resolution, authorization gates) so each rule is scannable rather than buried in one sentence.

Move the keyless oEmbed / measured-YouTube connector detail from the 'Data Sources' section into a short connectors reference file (alongside the existing per-platform vetting reference), keeping only the one-line capability summary inline in SKILL.md.

DimensionReasoningScore

Conciseness

The body is mostly efficient — no explanations of concepts Claude already knows — but could be meaningfully tightened: the Skill Contract "Writes" bullet is a single ~180-word sentence, and the opaque-ref/identity and separate-authorization rules are restated nearly verbatim in the Skill Contract and again in Steps 2, 4, and 5. It is not a 2 because there is no concept over-explanation or padded filler, only redundancy and over-long sentences.

3 / 5

Actionability

Concrete executable guidance is present — oEmbed endpoint URLs, the exact `python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/youtube.py" channel @handle` command, `~~` connector placeholders, and per-step template blocks in a real references/templates.md file. It falls short of fully copy-paste-ready coverage because most per-step field formats are deferred to the reference files and the referenced connector script is not part of this bundle.

4 / 5

Workflow Clarity

Six steps are clearly sequenced with explicit validation checkpoints and feedback loops: stop with NEEDS_INPUT when required criteria are missing, screening filters in Step 3, refresh logic in Step 4 (stale/unknown required fields force `triage_state: NEEDS_REFRESH`, `ranking_status: NOT_RANKED`, and `NEEDS_INPUT`), and a "Done when" checklist plus partial-checkpoint rules. This matches the top anchor's explicit-validation, error-recovery pattern rather than the minor-validation-gaps level of 4.

5 / 5

Progressive Disclosure

Structure is good: all three local references (templates.md, platform-vetting.md, creator-dossier.md) exist, contain the content claimed (step fill-in blocks and the worked-example anchor are verifiably in templates.md), and are one level deep, clearly signaled, and summarized in a Reference Materials list. It is not a 5 because dense policy prose (the privacy/identity contract, oEmbed/YouTube connector detail) is inlined in SKILL.md where a reference file could carry it, and several referenced paths (../../../references/skill-contract.md, CONNECTORS.md, scripts/connectors) resolve outside this bundle and cannot be verified.

4 / 5

Total

16

/

20

Passed

Description

92%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.

A strong description: concrete capabilities, explicit quoted trigger phrases in both English and Chinese, and a sharp not-for boundary that disambiguates it from the sibling fit-scorer skill. The only weakness is modest synonym coverage (missing terms like KOL or influencer research) that leaves a few natural user phrasings uncovered.

DimensionReasoningScore

Specificity

The description lists four concrete, specific actions — "produces a multi-platform candidate pool, per-influencer evidence profiles, authenticity red-flag screening, and a Fit-readiness queue without action ranking" — giving comprehensive coverage of the skill's outputs. It exceeds the minor-gaps level of a 4 because every named capability is a distinct concrete action rather than a generic category.

5 / 5

Completeness

It explicitly answers both questions: what it does (candidate pool, evidence profiles, red-flag screening, readiness queue) and when to use it, with concrete quoted trigger phrases. A clear not-for boundary ("Not for STAR scoring or ranking a known shortlist — use fit-scorer") further sharpens both, matching the top anchor rather than the 'when could be more specific' level of 4.

5 / 5

Trigger Term Quality

Natural trigger phrases are present and quoted ("find influencers", "build an influencer list", "discover creators in [niche]") plus Chinese synonyms ("达人挖掘/找达人/创作者名单"), matching the good-coverage anchor. It falls short of 5 because common variations users would naturally say — e.g. "KOL", "influencer research", "find creators" — are missing, and "Fit-readiness" is internal jargon.

4 / 5

Distinctiveness Conflict Risk

The niche is clear (influencer/creator discovery from scratch) and the explicit disambiguation "Not for STAR scoring or ranking a known shortlist — use fit-scorer" minimizes overlap with the closely related scoring skill. This is the distinct-triggers, minimal-conflict case rather than the minor-overlap case of 4.

5 / 5

Total

19

/

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.

Validation — 12 / 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

Path

influencer/scout/influencer-discovery/SKILL.md

Reviewed

Table of Contents

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