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apify-brand-reputation-monitoring

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

56

Quality

64%

Does it follow best practices?

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Adds up to 20 points to the overall score

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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

75%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 content is a solid, actionable playbook: concrete commands, a clear sequenced workflow with error recovery, and good section structure. It falls just short of top marks on small gaps — no example input payload, no output verification step, and a few trimmable phrases.

DimensionReasoningScore

Conciseness

The body is efficient — dense command blocks, a lookup-style actor table, and no explanations of concepts Claude already knows — with only minor trimmable padding: the opening sentence duplicates the description verbatim, the "(No need to check it upfront)" parenthetical is unclear, and "Based on character of use case" is vague filler.

4 / 5

Actionability

Guidance is mostly executable: complete mcpc and node commands for all three output modes, with placeholders (ACTOR_ID, JSON_INPUT) explicitly called out for substitution. The gap keeping it from 5 is the absence of a concrete example JSON_INPUT payload for any actor.

4 / 5

Workflow Clarity

A clear 5-step sequence with a copyable progress checklist, an Error Handling section that maps failures to recovery actions, and a Step 5 reporting step (counts, file location, next steps). Minor validation gap: no checkpoint verifying the output file itself after a run.

4 / 5

Progressive Disclosure

Well-organized sections with a one-level-deep script reference (${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js); the 18-row actor table is inline but directly consumed by Step 1 and reasonably placed. No nested or buried references, though the table is borderline content that could live in a references file.

4 / 5

Total

16

/

20

Passed

Description

53%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 concise, third-person, and names a specific domain, but it is incomplete: it answers "what" without any "when" guidance and lacks key synonyms like reputation and sentiment that would help trigger selection. It sits solidly at the middle of the scale with a slight edge on distinctiveness.

Suggestions

Append an explicit trigger clause, e.g. "Use when monitoring brand reputation, review sentiment, or ratings across platforms like Google Maps, Facebook, Instagram, Booking.com, TripAdvisor, or YouTube."

Add natural synonyms such as "reputation", "sentiment", and "social listening" so the description matches how users actually phrase these requests.

Mention the downstream capabilities the skill provides (choosing an actor, exporting to CSV/JSON, summarizing reputation signals) to lift specificity beyond a single scrape verb.

DimensionReasoningScore

Specificity

"Scrape reviews, ratings, and brand mentions from multiple platforms" names the domain and its data objects but describes a single action type applied to three nouns; it omits concrete steps the skill actually performs (schema lookup, CSV/JSON export, summarization), matching the 1-2-concrete-actions anchor rather than the several-specific-actions anchor.

3 / 5

Completeness

The "what" is clear (scrape reviews, ratings, and brand mentions via Apify Actors), but there is no "Use when..." clause or equivalent trigger guidance, which the judging guidelines cap at 3.

3 / 5

Trigger Term Quality

"reviews", "ratings", and "brand mentions" are natural user phrases, but common synonyms are absent — notably "reputation" (the skill's own title concept), "sentiment", and the platform names (Google, Facebook, Instagram) that users would actually say.

3 / 5

Distinctiveness Conflict Risk

"using Apify Actors" plus the reviews/brand-mentions niche gives it a mostly distinct trigger profile with only minor overlap risk against generic scraping or data-export skills, not the clear-niche minimal-conflict level of a 5.

4 / 5

Total

13

/

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
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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