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apify-influencer-discovery

Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.

60

Quality

76%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/apify-influencer-discovery/SKILL.md

The canonical home for this skill is apify-influencer-discovery in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

71%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, actionable workflow with concrete commands and clear sequencing. The main gaps are the missing 'run_actor.js' script in the bundle (the workflow's central dependency) and the absence of a concrete input example or post-run validation step.

Suggestions

Ship the referenced run_actor.js script inside the skill's scripts/ directory (and fix the path so it resolves within the bundle), since every execution step depends on it.

Add one concrete example of a JSON_INPUT value (e.g., for the Instagram profile scraper) so the --input argument is copy-paste ready.

Insert a validation checkpoint between Step 4 and Step 5 — confirm the run succeeded and output is non-empty before summarizing results.

DimensionReasoningScore

Conciseness

The body is lean — a selection table, ready-to-run commands, and short step descriptions with almost no explanation of concepts Claude already knows. Minor trimmable cruft remains (the odd "(No need to check it upfront)" note and the vague "Based on character of use case"), so it fits 'efficient; minor instances of over-explanation' rather than the fully lean score-5 anchor.

4 / 5

Actionability

Guidance is mostly executable: concrete bash commands for schema fetching and three ready-to-run script invocations with flags, plus a remediation list per error. It stops short of score 5 because placeholders like 'JSON_INPUT' lack a concrete example input, so the user must construct the argument without a template.

4 / 5

Workflow Clarity

A clear 5-step sequenced workflow with a copy-trackable checklist, an explicit decision table for Step 1, and an error-handling section covering failure recovery — matching 'clear sequence with most checkpoints present'. It is not 5 because there is no validation step between running the Actor and summarizing (e.g., verifying the run succeeded or output is non-empty before reporting), and not 3 because the operations are non-destructive and remediation guidance is present.

4 / 5

Progressive Disclosure

The body relies on ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js, but no scripts/ (or references/) directory exists in the bundle — a dangling reference that leaves the core execution step unverifiable. All content (including the 15-actor table) is inlined in SKILL.md with no external references, fitting 'some structure but could be better organized; references present but not clearly signaled'.

3 / 5

Total

15

/

20

Passed

Description

71%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, specific description with concrete actions and good natural keywords, written in third person. Its main weakness is the absence of any explicit 'Use when...' trigger guidance, which caps completeness at 3.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user wants to find influencers, vet creators for sponsorships, or check follower authenticity on Instagram, Facebook, YouTube, or TikTok."

Include common user phrasings like "content creator", "creator marketing", or "sponsorship" to broaden natural trigger coverage.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance" — plus four named platforms, giving comprehensive, specific coverage rather than generic domain language.

5 / 5

Completeness

The "what" is clear (find/evaluate/verify/track influencers across platforms) but there is no "Use when..." or equivalent explicit trigger guidance, which per the judging guidelines caps completeness at 3. It fits the anchor 'Has a clear what but when is missing or only weakly implied' — not 4 because no when-clause exists at all, and not 2 because the what is concrete, not vague.

3 / 5

Trigger Term Quality

Natural terms users would say are present ("influencers", "brand partnerships", "authenticity", "collaboration", and all four platform names), but common variations like "content creator", "creator marketing", or "sponsorship" are missing. Good coverage with a few natural terms absent, matching the score-4 anchor.

4 / 5

Distinctiveness Conflict Risk

The influencer-marketing niche with named social platforms is mostly distinct with clear triggers, but it could overlap with generic social-media scraping or marketing-analytics skills, matching 'mostly distinct; minor overlap risk with closely related skills'.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/apify-influencer-discovery/SKILL.md

Reviewed

Table of Contents

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