algolia-search
Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning
56
48%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/antigravity-algolia-search/SKILL.mdQuality
Discovery
54%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 benefits from strong, specific product-level keywords (Algolia, React InstantSearch) that make it highly distinctive and easy to trigger on relevant queries. However, it lacks a 'Use when...' clause and reads more like a topic list than a description of concrete capabilities, significantly hurting its completeness and specificity scores.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about Algolia search setup, configuring search indices, building search UIs with React InstantSearch, or tuning search relevance.'
Replace abstract topic labels with concrete actions, e.g., 'Configure Algolia search indices, build faceted search UIs with React InstantSearch, set custom ranking rules, and optimize relevance scoring.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (Algolia search) and some actions/areas like 'implementation', 'indexing strategies', 'React InstantSearch', and 'relevance tuning', but these are more like topic areas than concrete actions. It doesn't list specific operations like 'configure search indices', 'build faceted search UI', or 'set ranking rules'. | 2 / 3 |
Completeness | Describes the 'what' at a high level but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' itself is also somewhat weak, making this a 1. | 1 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'Algolia', 'search', 'indexing', 'React InstantSearch', and 'relevance tuning'. These are terms developers would naturally use when seeking help with Algolia integration. | 3 / 3 |
Distinctiveness Conflict Risk | Algolia is a very specific product/service, and the combination of 'Algolia', 'React InstantSearch', and 'relevance tuning' creates a clear niche that is unlikely to conflict with other skills. | 3 / 3 |
Total | 9 / 12 Passed |
Implementation
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill excels at actionability with high-quality, executable code examples covering the full Algolia integration surface area. However, it is severely bloated—everything is crammed into a single file with no progressive disclosure, and many sections include unnecessary explanations. The Sharp Edges and Validation Checks sections are particularly wasteful, listing items with only severity labels and no actionable guidance.
Suggestions
Split the skill into an overview SKILL.md with brief descriptions and links to separate files (e.g., INDEXING.md, SSR.md, SECURITY.md, RELEVANCE.md) for each major pattern's full code examples.
Remove or drastically condense the Sharp Edges section—either add actionable mitigation steps for each item or remove the entries that just repeat what's already covered in Anti_patterns sections.
Eliminate the Validation Checks section or convert it into a concise checklist format; currently it duplicates anti-patterns content with no additional value.
Remove explanatory text that Claude already knows (e.g., 'Key types: Admin API Key: Full control...', widget type lists) and let the code examples speak for themselves.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~500+ lines, with significant redundancy across sections. It explains concepts Claude already knows (what faceting is, what API keys are, widget types lists). The anti-patterns sections repeat information already shown in code examples. Sharp Edges and Validation Checks sections list items with no actionable detail beyond severity labels, wasting tokens. | 1 / 3 |
Actionability | The code examples are fully executable, copy-paste ready TypeScript/React code covering client setup, indexing, SSR, security, relevance tuning, faceted search, and autocomplete. Each section provides concrete, working implementations with proper imports and realistic patterns. | 3 / 3 |
Workflow Clarity | Individual sections are clear but there's no overall workflow sequence connecting them (e.g., configure index → index data → validate → build UI). The full reindex function includes an atomic swap pattern which is good, but the Sharp Edges and Validation Checks sections lack actionable steps or verification procedures—they're just labels with severity levels. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no references to separate files for detailed topics. All seven major patterns with full code examples are inline, making this extremely long. The content would benefit enormously from splitting code examples into separate files and keeping SKILL.md as an overview with navigation links. | 1 / 3 |
Total | 7 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (921 lines); consider splitting into references/ and linking | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Repository
- boisenoise/skills-collections
- Commit
636b862
- Reviewed
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