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twitter-mention-tracker

Search and scrape Twitter/X posts using Apify. Use when you need to find tweets, track brand mentions, monitor competitors on Twitter, or analyze Twitter discussions. Uses Twitter native search syntax (since:/until:) for reliable date filtering.

73

Quality

92%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%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.

Excellent, lean skill content: fully executable commands, a complete CLI reference, and a well-organized single-script bundle with no padding or beginner-level explanation. The only weakness is mild redundancy in explaining the date-filtering approach three times.

DimensionReasoningScore

Conciseness

The body is efficient with no explanation of concepts Claude already knows, but the since:/until: date-embedding rationale is repeated across three places (the "Date Filtering" section, "How the Script Works" step 1, and the Quick Start comment), which is a minor instance of content that could be trimmed. Not a 5 because that redundancy prevents 'every token earns its place'; well above the 3 anchor since almost everything is actionable rather than explanatory.

4 / 5

Actionability

Fully executable, copy-paste-ready commands in Quick Start and Common Workflows, a complete CLI reference table with flags and defaults, the raw actor JSON input, and a concrete output schema example. The common cases (date-ranged search, summary output, no-date search) are all covered, matching the 5 anchor; the 4 anchor would require minor gaps, and none are present.

5 / 5

Workflow Clarity

This is a simple, single-purpose skill whose single action (run the script with a query) is unambiguous, and "How the Script Works" lays out the internal sequence (build term → run actor → poll → dedup → filter → sort → output). The operation is read-only scraping, not destructive or mutating, so the validation-cap guideline does not apply, and the script itself surfaces failure states (FAILED/ABORTED/TIMED-OUT, timeout).

5 / 5

Progressive Disclosure

The bundle is one script (scripts/search_twitter.py), which exists and is referenced directly in every example command, and all inline content (CLI table, output format, workflows) is compact enough to belong in the overview. Structure is well-organized with clear section headers and no content that should be split out to separate files or nested references, matching the 5 anchor's clear-overview criterion.

5 / 5

Total

19

/

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.

A strong description: explicit what-and-when structure, natural trigger phrases, third-person voice, and a distinctive niche. Minor room to grow on specificity and trigger synonyms (e.g., X posts, social listening, hashtags), but nothing vague or over-claimed.

DimensionReasoningScore

Specificity

The description lists several concrete actions — "Search and scrape Twitter/X posts using Apify", "find tweets, track brand mentions, monitor competitors on Twitter, or analyze Twitter discussions" — so it sits at the 'several specific actions; minor gaps' anchor. It is not a 5 because the actions are generic verbs with no coverage of the skill's actual capabilities (date-range filtering via since:/until: is mentioned only as a mechanism note, and output/sorting features are absent).

4 / 5

Completeness

It explicitly answers both: what ("Search and scrape Twitter/X posts using Apify") and when ("Use when you need to find tweets, track brand mentions, monitor competitors on Twitter, or analyze Twitter discussions") with concrete trigger phrases. This matches the 5 anchor directly; the 4 anchor would require the 'when' to be less explicit or specific, which it is not.

5 / 5

Trigger Term Quality

Natural user phrases are present — "find tweets", "track brand mentions", "monitor competitors on Twitter", "analyze Twitter discussions" — giving good keyword coverage. It falls short of the 5 anchor because common variations like "X posts", "social listening", "@handle", or "hashtags" are missing, and "Apify" alone covers the technical side.

4 / 5

Distinctiveness Conflict Risk

It occupies a clear niche (Twitter/X scraping via a specific Apify actor) with distinct triggers like "tweets", "brand mentions", and "competitor monitoring on Twitter". Conflict risk with generic search or social-media skills is minimal; not the 4 anchor since no meaningful overlap with a closely related skill's triggers is apparent.

5 / 5

Total

18

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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