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algolia-search

Expert patterns for Algolia search implementation, indexing strategies, React InstantSearch, and relevance tuning

48

Quality

53%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/antigravity-algolia-search/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

53%Weight 40%Scale 1-5

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

The body is a clean progressive-disclosure pointer: one real, well-structured reference file and an explicit mandate to treat its safety and validation requirements as binding. Its weaknesses are padded trigger phrasing, a duplicated description line, and the absence of any section index or inline critical checks that would make focused loading and standalone use actionable.

Suggestions

Collapse the ten repeated 'User mentions or implies:' lines into a single line ('Use when the user mentions: algolia, instantsearch, typeahead, autocomplete, faceted search, search index, search-as-you-type...') and delete the line that duplicates the frontmatter description.

Add a brief section index of the guide (Patterns, Sharp Edges, Validation Checks, Collaboration) to the body so 'load the relevant sections' names the sections to load.

Surface one or two critical validation checks inline (e.g., never ship the admin API key to the client) so the body is not a pure pointer for the highest-risk pitfalls.

DimensionReasoningScore

Conciseness

The body is short, but the phrase 'User mentions or implies:' is repeated verbatim ten times and line 12 restates the frontmatter description verbatim — padding that could be collapsed to a single line. This is 'mostly efficient but includes some unnecessary explanation or could be tightened' rather than score 2, since the total token footprint is still small.

3 / 5

Actionability

The body gives one concrete, verifiable directive ('Read [the detailed guide](references/detailed-guide.md) before executing this skill') plus a focused vs. end-to-end loading strategy, and the referenced file is real and complete. It stays at 3 rather than 4 because the body itself contains no commands, code, or implementation steps — all executable guidance lives one file away.

3 / 5

Workflow Clarity

The reading sequence is unambiguous and validation is explicitly mandated ('Treat its safety, prerequisites, and validation requirements as mandatory'), but the body shows no implementation steps or validation checkpoints of its own, and the skill covers batch-sensitive indexing operations. This matches 'sequence present but checkpoints missing or implicit'.

3 / 5

Progressive Disclosure

A single well-signaled, one-level-deep reference (references/detailed-guide.md, ~25 KB, no nested references) with an appropriate split — the heavy patterns live outside SKILL.md. Kept below 5 because 'For focused work, load the relevant sections' is not supported by any section index in the body, leaving navigation to guesswork.

4 / 5

Total

13

/

20

Passed

Description

52%Weight 40%Scale 1-5

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 carves out a distinctive, low-conflict Algolia niche, but reads as a topic list rather than a capability statement and omits any explicit 'when to use' trigger guidance. Natural trigger phrases exist in the skill body but were not surfaced into the description.

Suggestions

Add an explicit trigger clause to the description, e.g. 'Use when the user mentions Algolia, InstantSearch, typeahead, autocomplete, faceted search, or building a search index.'

Replace the topic listing with concrete action verbs, e.g. 'Implements Algolia indexing pipelines, configures custom ranking and relevance, and builds React InstantSearch UIs.'

Include common user-side synonyms (search-as-you-type, autocomplete, typeahead) in the description itself so the frontmatter alone carries the triggers.

DimensionReasoningScore

Specificity

The description names the Algolia domain and four sub-areas ("search implementation, indexing strategies, React InstantSearch, and relevance tuning") but contains no action verbs describing what the skill does — a topic list closest to 'names the domain but actions are minimal or generic'. It is not a 3 because no concrete actions are stated at all, only subject areas.

2 / 5

Completeness

The 'what' is reasonably clear (Algolia search expertise across four areas) but there is no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3.

3 / 5

Trigger Term Quality

Relevant keywords are present ("Algolia", "InstantSearch", "indexing", "relevance tuning") but common natural phrases users would say — typeahead, autocomplete, faceted search, search-as-you-type — appear only in the body's When to Use list, not the description, matching 'some relevant keywords but missing common variations or synonyms'.

3 / 5

Distinctiveness Conflict Risk

"Algolia search" and "React InstantSearch" name a clear vendor-specific niche with distinct triggers and minimal risk of firing for unrelated search skills; nothing generic remains that would overlap broadly.

5 / 5

Total

13

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
boisenoise/skills-collections
Reviewed

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