apify-competitor-intelligence
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
76
66%
Does it follow best practices?
Impact
96%
2.66xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./plugins/antigravity-awesome-skills-claude/skills/apify-competitor-intelligence/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 listing concrete actions and specific platforms that carve out a well-defined niche. However, it lacks an explicit 'Use when...' clause, which limits its completeness score and could reduce Claude's ability to reliably select this skill. Adding trigger guidance and a few more natural user phrasings would elevate this description significantly.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about competitive analysis, competitor research, market benchmarking, or comparing businesses on these platforms.'
Include common user-facing trigger terms like 'competitive analysis', 'market research', 'competitor comparison', 'benchmarking', or 'spy on competitors' to improve keyword coverage.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'analyze competitor strategies, content, pricing, ads, and market positioning' across named platforms. These are concrete, actionable capabilities. | 3 / 3 |
Completeness | Clearly answers 'what does this do' with specific actions and platforms, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied by the capabilities listed, which per the rubric caps completeness at 2. | 2 / 3 |
Trigger Term Quality | Includes good platform names (Google Maps, Booking.com, Facebook, Instagram, YouTube, TikTok) and domain terms (competitor, pricing, ads), but misses common user phrasings like 'competitive analysis', 'market research', 'spy on competitors', or 'benchmark'. Some natural trigger terms are present but coverage of variations is incomplete. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of competitor analysis with specific platforms (Google Maps, Booking.com, social media) creates a clear niche. This is unlikely to conflict with generic marketing or analytics skills due to the specific platform enumeration and competitive intelligence focus. | 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 skill provides strong actionability with executable commands, specific Actor IDs, and clear CLI syntax for multiple output formats. However, it suffers from the massive inline Actor lookup table that hurts conciseness, and the workflow lacks validation checkpoints between steps (e.g., verifying schema fetch succeeded, validating input JSON). The generic limitations section adds no value and the progressive disclosure could be improved by extracting the Actor table to a reference file.
Suggestions
Extract the 30+ row Actor lookup table into a separate reference file (e.g., ACTORS.md) and keep only a few representative examples inline with a pointer to the full list.
Add validation checkpoints: after Step 2, verify the schema was fetched successfully before proceeding; after Step 4, check the run status and provide a retry/fix loop if it fails.
Remove the generic 'Limitations' section — these are boilerplate guardrails that Claude already knows and they waste tokens.
Remove the 'Prerequisites' note '(No need to check it upfront)' — if they don't need checking, just list them without the parenthetical.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The massive Actor lookup table (30+ rows) is useful reference but bloats the skill significantly. Some sections like 'Limitations' contain generic boilerplate that doesn't add value. The workflow steps and commands are reasonably tight, but the overall document could be more concise. | 2 / 3 |
Actionability | Provides fully executable bash commands for fetching schemas, running actors in multiple output formats, and clear CLI syntax with placeholder substitution. The Actor selection table gives specific Actor IDs, and the error handling section maps specific errors to specific fixes. | 3 / 3 |
Workflow Clarity | The 5-step workflow is clearly sequenced 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 if the run fails beyond checking the Apify console. For a multi-step process involving external API calls, explicit validation steps are needed. | 2 / 3 |
Progressive Disclosure | The skill references `${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js` suggesting a bundle structure exists, but no bundle files were provided to verify. The large Actor lookup table could be split into a separate reference file. The document is structured with clear sections but is somewhat monolithic with all content inline. | 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
4cc48db
- Reviewed
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