algolia-search
Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning
50
56%
Does it follow best practices?
Impact
—
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 terminology (Algolia, React InstantSearch) that makes it highly distinctive and provides good trigger terms. However, it lacks a 'Use when...' clause and reads more like a topic list than an actionable skill description with concrete operations. Adding explicit trigger guidance and more specific actions would significantly improve it.
Suggestions
Add a 'Use when...' clause such as 'Use when the user asks about Algolia search setup, configuring search indices, building search UIs with InstantSearch, or tuning search relevance.'
Replace abstract topic areas with concrete actions, e.g., 'Configure Algolia search indices, build faceted search UIs with React InstantSearch, set custom ranking rules, and optimize relevance scoring.'
Include common variations of trigger terms like 'search bar', 'autocomplete', 'search results', 'facets', 'filters' that users might naturally say.
| 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 vague, bringing it to 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
57%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 comprehensive, executable code examples covering the full Algolia integration surface area. However, it suffers from being a monolithic document that could be significantly improved by splitting into focused sub-files with a concise overview. The Sharp Edges and Validation Checks sections add bulk without proportional value since they lack remediation details, and the overall workflow connecting the pieces is implicit rather than explicit.
Suggestions
Split the skill into a concise SKILL.md overview (quick start + section summaries) with separate files for each pattern (e.g., INDEXING.md, SSR.md, SECURITY.md, RELEVANCE.md, FACETS.md, AUTOCOMPLETE.md)
Add a high-level workflow section at the top showing the recommended sequence: configure index settings → index data → build search UI → tune relevance, with validation checkpoints between steps
Either flesh out Sharp Edges with concrete remediation steps and code, or remove them since the Anti-patterns sections already cover the same ground more actionably
Consolidate the Validation Checks into a compact checklist table rather than verbose individual entries with repeated structure
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~500+ lines) with some redundancy. The Sharp Edges and Validation Checks sections list items without actionable detail (just severity labels), wasting tokens. Anti-patterns repeat information already shown in code examples. However, the code examples themselves are dense and useful, and it avoids explaining basic concepts Claude already knows. | 2 / 3 |
Actionability | Every major section includes fully executable, copy-paste-ready TypeScript/React code examples covering client setup, SSR integration, indexing, security, relevance tuning, faceted search, and autocomplete. The code is complete with imports, environment variable usage, and realistic patterns. | 3 / 3 |
Workflow Clarity | Individual patterns are clear, but there's no overarching workflow connecting the pieces (e.g., 'first configure index, then index data, then build UI'). The full reindex function shows an atomic swap sequence which is good, but the Sharp Edges and Validation Checks sections lack actionable remediation steps—they're just labels with severity. No explicit validation checkpoints for the indexing workflow (e.g., verify records indexed correctly before proceeding). | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no bundle files or references to separate documents. All seven major patterns, sharp edges, validation checks, collaboration triggers, and limitations are crammed into a single file. The content would benefit greatly from splitting code examples, configuration scripts, and reference material into separate files with clear navigation from a concise overview. | 1 / 3 |
Total | 8 / 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 (925 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
95574f3
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.