apify-market-research
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
72
66%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/apify-market-research/SKILL.mdQuality
Discovery
67%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 strong in specificity and distinctiveness, clearly naming concrete analysis actions and specific platforms that create a unique niche. However, it lacks an explicit 'Use when...' clause, which weakens completeness, and some trigger terms could be more aligned with natural user language (e.g., 'reviews', 'competitor analysis', 'market research').
Suggestions
Add a 'Use when...' clause such as 'Use when the user asks about market research, competitor analysis, review analysis, or business intelligence on Google Maps, Facebook, Instagram, Booking.com, or TripAdvisor.'
Include more natural user trigger terms like 'reviews', 'competitor analysis', 'market research', 'local business analysis', or 'social media insights' to improve discoverability.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation' across named platforms. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific analysis capabilities across named platforms, but there is no explicit 'Use when...' clause or equivalent trigger guidance, which caps this at 2 per the rubric guidelines. | 2 / 3 |
Trigger Term Quality | Includes relevant platform names (Google Maps, Facebook, Instagram, Booking.com, TripAdvisor) and domain terms (market conditions, pricing, consumer behavior), but missing common user phrases like 'competitor analysis', 'market research', 'reviews', or 'scrape'. Users might not naturally say 'product validation' or 'geographic opportunities'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of market analysis specifically across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor creates a clear niche that is unlikely to conflict with other skills. The platform-specific focus makes it highly distinctive. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
64%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a solid, actionable skill with concrete commands and a well-structured Actor selection table. Its main weaknesses are the lack of validation checkpoints integrated into the workflow (e.g., checking if the Actor run succeeded before summarizing) and some generic boilerplate in the limitations section. The progressive disclosure could be improved by linking to reference files for the Actor table and script documentation.
Suggestions
Add a validation step after Step 4 (e.g., check exit code or output file existence) and integrate error handling as a feedback loop within the workflow rather than a separate section.
Move the Actor lookup table to a separate reference file and link to it from the main skill to improve progressive disclosure and reduce inline bulk.
Remove the generic limitations section (lines like 'Do not treat the output as a substitute for environment-specific validation') as they don't add skill-specific value.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient but includes some unnecessary elements. The large Actor table is useful but could be more compact. The limitations section contains generic boilerplate that doesn't add value. The workflow checklist is reasonable but the step descriptions could be tighter. | 2 / 3 |
Actionability | Provides fully executable bash commands for each step, concrete Actor IDs in a lookup table, specific CLI flags and options, and clear command patterns for all three output formats. The mcpc command for fetching schemas is copy-paste ready. | 3 / 3 |
Workflow Clarity | Steps are clearly sequenced with a progress checklist, but there are no validation checkpoints between steps. After running the Actor (Step 4), there's no verification that the run succeeded before proceeding to summarize. The error handling section exists but isn't integrated into the workflow as feedback loops. | 2 / 3 |
Progressive Disclosure | The skill references external scripts (`run_actor.js`) and uses `${CLAUDE_PLUGIN_ROOT}/reference/scripts/` paths suggesting a broader file structure, but doesn't explicitly link to any reference documents. The Actor table is inline when it could potentially be a separate reference file, and there's no navigation to deeper documentation. | 2 / 3 |
Total | 9 / 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
| Criteria | Description | Result |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- sickn33/antigravity-awesome-skills
- Commit
1a9f5ac
- Reviewed
Table of Contents
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