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apify-market-research

Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.

56

Quality

65%

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-market-research/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%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 body is concise and actionable with a clear sequenced workflow and good error handling, but it is held back by a missing output-validation checkpoint and a referenced script that is absent from the bundle.

Suggestions

Add an explicit validation step to the workflow (e.g., after Step 4, verify the output file is non-empty and well-formed before summarizing) to satisfy the batch-operation feedback-loop requirement.

Ensure the referenced run_actor.js (and its reference/scripts/ directory) ships with the skill bundle, or inline the script's behavior so the commands are self-contained.

Condense the three near-identical output-format bash blocks into one block with a documented --format flag to reduce repetition.

DimensionReasoningScore

Conciseness

The body is lean with no padding about what Apify or the platforms are; a dense actor-selection table and direct bash commands assume Claude's competence, with only minor repetition across the three output-format examples that could be tightened.

4 / 5

Actionability

Concrete, copy-paste bash commands with real actor IDs and flag examples are provided, but placeholders (ACTOR_ID, JSON_INPUT) must be substituted and the referenced run_actor.js script is not present in the bundle.

4 / 5

Workflow Clarity

A clear five-step sequence with a progress checklist and an error-handling section is present, but this batch data-extraction workflow lacks an explicit validation/verification checkpoint, which caps workflow clarity at 3 per the guidelines.

3 / 5

Progressive Disclosure

Sections are reasonably organized (Prerequisites, Workflow, Steps, Error Handling), but the only external reference (${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js) is not present in the bundle, so the reference is neither verifiable nor clearly signaled.

3 / 5

Total

14

/

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.

The description is specific and distinctive, listing concrete research areas and platforms, but it omits any explicit "Use when..." trigger guidance, capping completeness. Adding a trigger clause would lift the weakest dimension.

Suggestions

Append a "Use when..." clause naming the user situations that should trigger this skill (e.g., "Use when the user wants to research market conditions, pricing, or consumer behavior across Google Maps, Facebook, Instagram, Booking.com, or TripAdvisor").

Vary the action verbs beyond the single "Analyze" to surface distinct capabilities (e.g., extract, compare, validate) for stronger specificity.

Add common natural synonyms such as "scraping" or "lead generation" to broaden trigger-term coverage.

DimensionReasoningScore

Specificity

The description enumerates several concrete analytical areas ("market conditions, geographic opportunities, pricing, consumer behavior, and product validation") across five named platforms, giving comprehensive domain coverage, though the single verb "Analyze" is reused rather than listing multiple distinct actions.

4 / 5

Completeness

The "what" is clear and specific, but there is no "Use when..." clause or equivalent explicit trigger guidance, which per the guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Natural terms a user would say ("market conditions", "pricing", "consumer behavior") plus platform names (Google Maps, Facebook, Instagram, Booking.com, TripAdvisor) give good keyword coverage, but common synonyms like "scraping" or "lead generation" are absent.

4 / 5

Distinctiveness Conflict Risk

The Apify-driven market-research framing tied to specific platforms carves a clear niche with minimal conflict risk, with only minor overlap against a generic market-research 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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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