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algolia-search

Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning Use when: adding search to, algolia, instantsearch, search api, search functionality.

46

Quality

48%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./plugins/antigravity-bundle-integration-apis/skills/algolia-search/SKILL.md

The canonical home for this skill is algolia-search in sickn33/agentic-awesome-skills

SKILL.md
Quality
Evals
Security

Quality

Content

14%Scale 1-3

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is essentially an outline or stub rather than a functional skill. It lacks any executable code examples, contains a completely placeholder sharp edges table with no real content, and provides only abstract descriptions of Algolia concepts without actionable guidance. The 'When to Use' section adds no value.

Suggestions

Add complete, executable code examples for at least the React InstantSearch setup and indexing operations (e.g., a full component with useSearchBox/useHits, and a batch indexing script with algoliasearch client)

Replace the placeholder sharp edges table with actual issues—e.g., 'API key exposed in client bundle → Use search-only API key, never admin key' or 'Stale index after DB update → Implement webhook-based sync'

Add a concrete workflow with validation steps for the indexing process, such as: create index → push batch → verify record count → configure searchable attributes → test query

Either remove the 'When to Use' section or replace it with specific trigger conditions (e.g., 'Use when adding full-text search to a React/Next.js app with <10M records')

DimensionReasoningScore

Conciseness

The content is moderately concise but includes some unnecessary framing (e.g., 'Indexing strategies for keeping Algolia in sync with your data') and the 'When to Use' section is a meaningless tautology. The sharp edges table is entirely placeholder content, wasting tokens.

2 / 3

Actionability

There is no executable code anywhere in the skill. It lists hook names and concepts but provides no concrete code examples, no import statements, no component setup, and no copy-paste ready snippets. The sharp edges table contains only placeholder 'Issue' and 'See docs' entries with zero actual guidance.

1 / 3

Workflow Clarity

The indexing section lists three approaches but provides no actual commands, no validation steps, and no sequenced workflow. The SSR section lists considerations without showing how to implement them. There are no feedback loops or checkpoints for any process.

1 / 3

Progressive Disclosure

The content is a flat list of topics with no references to external files, no links to detailed guides, and no clear navigation structure. It's neither a concise overview pointing elsewhere nor a comprehensive standalone guide—it's an incomplete middle ground.

1 / 3

Total

5

/

12

Passed

Description

82%Scale 1-3

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a reasonably good description that clearly identifies its domain (Algolia search) and includes an explicit 'Use when' clause with relevant trigger terms. Its main weaknesses are that the capability descriptions lean toward topic areas rather than concrete actions, and some trigger terms like 'search functionality' are generic enough to potentially conflict with other search-related skills.

Suggestions

Replace topic-area language with concrete actions, e.g., 'Configures Algolia indices, implements React InstantSearch components, tunes ranking and relevance rules, manages searchable attributes and facets.'

Add more Algolia-specific trigger terms to reduce conflict risk, e.g., 'algolia dashboard, search index, faceted search, algolia api key, searchable attributes, ranking formula'.

DimensionReasoningScore

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 specific actions (e.g., 'configure faceted search', 'set up searchable attributes').

2 / 3

Completeness

Clearly answers both 'what' (Algolia search implementation, indexing strategies, React InstantSearch, relevance tuning) and 'when' with an explicit 'Use when:' clause listing trigger scenarios.

3 / 3

Trigger Term Quality

Includes good natural keywords users would say: 'algolia', 'instantsearch', 'search api', 'search functionality', 'adding search to'. These cover the most common ways a user would phrase requests related to Algolia search.

3 / 3

Distinctiveness Conflict Risk

The Algolia-specific terms ('algolia', 'instantsearch') are distinctive, but broader terms like 'search functionality' and 'search api' could overlap with other search-related skills (e.g., Elasticsearch, generic search implementations).

2 / 3

Total

10

/

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.

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

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