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 ./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 define a clear niche. Its main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. Adding common user-facing trigger terms and variations would also improve discoverability.
Suggestions
Add a 'Use when...' clause, e.g., 'Use when the user asks for competitive analysis, competitor research, market comparison, or wants to analyze rivals on social media or booking platforms.'
Include natural trigger term variations such as 'competitive analysis', 'competitor research', 'market research', 'social media competitor tracking', or 'ad analysis'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions ('analyze competitor strategies, content, pricing, ads, and market positioning') and names specific platforms (Google Maps, Booking.com, Facebook, Instagram, YouTube, TikTok). | 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, which caps this dimension at 2 per the rubric. | 2 / 3 |
Trigger Term Quality | Includes relevant keywords like 'competitor', 'pricing', 'ads', 'market positioning', and specific platform names that users might mention. However, it misses common variations like 'competitive analysis', 'competitor research', 'social media analysis', 'ad spy', or 'market research'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of competitor analysis with specific platforms (Google Maps, Booking.com, Facebook, Instagram, YouTube, TikTok) creates a clear niche that is unlikely to conflict with generic analytics or social media management skills. | 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 actionable, executable commands and a clear multi-step workflow for competitor intelligence gathering across many platforms. Its main weaknesses are the oversized inline Actor lookup table that hurts conciseness and progressive disclosure, and the lack of validation checkpoints between workflow steps (e.g., verifying schema fetch success before proceeding, validating JSON input).
Suggestions
Move the Actor lookup table to a separate reference file (e.g., ACTORS.md) and reference it from the main skill with a brief summary of categories.
Add a validation checkpoint after Step 2 to verify the schema was fetched successfully before proceeding (e.g., 'Confirm the output contains inputSchema before continuing').
Add a validation step after Step 4 to check the run status and handle partial results or empty datasets before summarizing.
Remove the redundant 'Best For' column in the Actor table since it largely duplicates the 'User Need' column.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The massive Actor lookup table (30+ rows) is useful reference but could be in a separate file. The boilerplate limitations section and some descriptions ('Best For' column often just restates the 'User Need' column) add unnecessary tokens. However, the commands and workflow steps are reasonably tight. | 2 / 3 |
Actionability | Provides fully executable bash commands for fetching schemas, running actors in multiple output formats, and clear CLI syntax with proper flag usage. The commands are copy-paste ready with clear placeholder substitution patterns. | 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 for handling partial or unexpected results from the Actor run. | 2 / 3 |
Progressive Disclosure | The skill references external scripts (`run_actor.js`) appropriately, but the 30+ row Actor lookup table should be in a separate reference file rather than inline. The skill is a monolithic document that would benefit from splitting the Actor catalog into a referenced file. | 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
b938655
- Reviewed
Table of Contents
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