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apify-brand-reputation-monitoring

Scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.

57

Quality

66%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/apify-brand-reputation-monitoring/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

64%Scale 1-3

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

This skill provides strong actionability with concrete commands and a comprehensive Actor lookup table, making it practical for brand reputation monitoring tasks. However, it lacks validation checkpoints in its workflow (e.g., verifying schema fetch, validating input JSON before execution), and the large inline Actor table and repetitive command blocks reduce conciseness. The boilerplate Limitations section adds no value.

Suggestions

Add a validation step after fetching the Actor schema (Step 2) to verify the response contains expected fields before proceeding, and add input validation before running the script in Step 4.

Move the Actor lookup table to a separate reference file (e.g., ACTORS.md) and link to it from the main skill to improve conciseness and progressive disclosure.

Consolidate the three nearly identical script invocations into a single template with a note about the --output and --format flags being optional for quick-answer mode.

Remove or replace the generic Limitations section with skill-specific constraints (e.g., rate limits, platform-specific quirks, data freshness expectations).

DimensionReasoningScore

Conciseness

The content is mostly efficient but includes some unnecessary elements. The massive Actor table (18 rows) could be more concise, and the Limitations section contains generic boilerplate that doesn't add value. The three nearly identical script invocations for different formats could be condensed.

2 / 3

Actionability

Provides fully executable bash commands for each step, concrete Actor IDs in a lookup table, specific CLI flags, and clear input/output patterns. The commands are copy-paste ready with clear placeholder substitution points.

3 / 3

Workflow Clarity

The workflow has a clear 5-step sequence with a progress checklist, but lacks validation checkpoints. There's no step to verify the Actor schema was fetched correctly, no validation of the JSON input before running, and no feedback loop for handling partial results or retrying failed runs.

2 / 3

Progressive Disclosure

The skill references scripts at `${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js` but no bundle files are provided to verify these exist. The Actor table is inlined rather than being in a separate reference file, making the main skill longer than necessary. However, the section structure is logical and navigable.

2 / 3

Total

9

/

12

Passed

Description

67%Scale 1-3

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 specific about what it does and uses a distinctive tool reference (Apify Actors), making it clearly identifiable. However, it lacks an explicit 'Use when...' clause which caps completeness, and could benefit from more natural trigger terms that users would commonly use when requesting this type of task.

Suggestions

Add a 'Use when...' clause, e.g., 'Use when the user wants to scrape or collect reviews, ratings, or brand mentions from websites, or mentions Apify.'

Include additional natural trigger terms and platform examples, e.g., 'web scraping, crawling, Yelp reviews, Google Reviews, Trustpilot, social media monitoring, reputation tracking.'

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: 'scrape reviews, ratings, and brand mentions from multiple platforms using Apify Actors.' This names the domain (web scraping), specific data types (reviews, ratings, brand mentions), and the tool (Apify Actors).

3 / 3

Completeness

Clearly answers 'what does this do' (scrape reviews, ratings, brand mentions using Apify Actors), but lacks an explicit 'Use when...' clause or equivalent trigger guidance for when Claude should select this skill.

2 / 3

Trigger Term Quality

Includes some relevant keywords like 'scrape', 'reviews', 'ratings', 'brand mentions', and 'Apify', but misses common variations users might say such as 'sentiment', 'feedback', 'web scraping', 'crawl', or specific platform names (e.g., 'Yelp', 'Google Reviews', 'Trustpilot').

2 / 3

Distinctiveness Conflict Risk

The combination of scraping reviews/ratings/brand mentions specifically via Apify Actors creates a clear niche that is unlikely to conflict with other skills. The mention of Apify Actors as the specific tooling adds strong distinctiveness.

3 / 3

Total

10

/

12

Passed

Validation

90%

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

Validation — 10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

10

/

11

Passed

Repository
popey/claude-code-skills
Reviewed

Table of Contents

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