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apify-brand-reputation-monitoring

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

Quality

76%

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

77%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, largely executable skill body with strong workflow sequencing, pre-run validation, and error-recovery loops appropriate to a paid batch operation. The main weaknesses are a monolithic single-file layout whose only script reference points to a file absent from the bundle, placeholder-only command examples, and two dense boundary paragraphs that could be tightened or split out.

Suggestions

Ship the referenced script (e.g. reference/scripts/run_actor.js) in the bundle or correct the path so the primary command is actually runnable as written.

Add one worked example with a real actor ID and a concrete --input JSON payload so the commands become copy-paste ready.

Move the 20-row actor catalog into a one-level-deep reference file (e.g. references/actors.md) with a 'See ACTORS.md' pointer, and convert the two run-on 'Run Boundaries' paragraphs into scannable bullets.

DimensionReasoningScore

Conciseness

The body is operational throughout — no re-teaching of concepts Claude already knows, an efficient actor-selection table, and tight step blocks — matching 'efficient; minor instances of over-explanation that could be trimmed'. It is not 5 because the two dense run-on 'Run Boundaries' paragraphs mix billing, safety, dedup, and comparability caveats that could be tightened into scannable bullets.

4 / 5

Actionability

Concrete executable commands are given per output format (node --env-file=.env ... run_actor.js with --actor/--input/--output/--format flags), plus prerequisite checks and per-error remediation, matching 'mostly executable guidance; concrete code or commands with minor gaps'. It is not 5 because the commands contain unresolved placeholders (ACTOR_ID, JSON_INPUT) with no worked example of a real input, and the referenced script file is absent from the bundle.

4 / 5

Workflow Clarity

The five-step workflow has explicit validation before paid runs (verify .env/token, fetch and verify the actor schema, confirm scope/limits with the user, start with a small input limit), a copyable progress checklist, and feedback loops in Error Handling (Run FAILED → inspect console link; Timeout → inspect run ID before retrying to avoid duplicate charges), matching the anchor 'clear sequence with explicit validation steps; feedback loops for error recovery; checklists'. As a batch/paid operation it avoids the missing-validation cap because checkpoints are present at every phase.

5 / 5

Progressive Disclosure

Scored against the actual bundle structure: no references/, scripts/, or assets/ directories exist, so the sole referenced path ("reference/scripts/run_actor.js") is dangling and cannot resolve. Content is monolithic in one ~127-line file — above the under-50-line simple-skill exception — with a 20-row actor catalog inlined that clearly belongs in a reference file, matching 'some structure but could be better organized... content that should be separate is inline'. It is not 2 because section headers, the checklist, and per-step organization make navigation genuinely workable.

3 / 5

Total

16

/

20

Passed

Description

66%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 concise, third-person description with concrete named actions and a distinct Apify niche. Its main deficiency is the complete absence of a 'when to use' trigger clause, which caps completeness, plus missing natural synonyms (reputation, sentiment) and platform names that would strengthen triggers.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when the user asks to monitor brand reputation, scrape reviews or ratings, or track brand mentions on platforms like Google Maps, Booking, TripAdvisor, Facebook, Instagram, YouTube, or TikTok.'

Include natural synonyms users would say — 'brand reputation', 'sentiment', 'review monitoring' — alongside the existing 'reviews', 'ratings', and 'brand mentions'.

Optionally name the concrete actions end-to-end (select actor, run scrape, export CSV/JSON, summarize reputation signals) to lift specificity from several-actions to comprehensive coverage.

DimensionReasoningScore

Specificity

"Scrape reviews, ratings, and brand mentions from multiple platforms" lists several concrete actions (scrape reviews, ratings, brand mentions) in a named domain (Apify Actors), matching the 'several specific actions; minor gaps in coverage' anchor. It is not 5 because it omits other capabilities the body shows (exporting results, choosing actors, summarizing) and does not name any specific platforms.

4 / 5

Completeness

The 'what' is clear (scrape reviews/ratings/brand mentions via Apify Actors) but there is no 'Use when...' clause or equivalent explicit trigger guidance, which the judging guidelines cap at 3. Per anti-drift, it is not 4 because the 'when' is entirely absent rather than merely under-specified.

3 / 5

Trigger Term Quality

Natural phrases users would say — "reviews", "ratings", "brand mentions", "Apify Actors" — give good keyword coverage per the anchor 'good keyword coverage; a few natural terms missing'. It misses common synonyms and variations users would likely use: "reputation", "sentiment", "monitor", and specific platform names (Google Maps, Booking, Facebook, TikTok), keeping it below 5.

4 / 5

Distinctiveness Conflict Risk

"using Apify Actors" carves out a mostly distinct niche with minor overlap risk against closely related generic scraping skills, matching the 'mostly distinct; minor overlap risk' anchor. It is not 5 because 'multiple platforms' is broad and no explicit trigger phrase further separates it from a general Apify-scraping skill.

4 / 5

Total

15

/

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

Path

skills/apify-brand-reputation-monitoring/SKILL.md

Reviewed

Table of Contents

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