similarity-search-patterns

Implement efficient similarity search with vector databases. Use when building semantic search, implementing nearest neighbor queries, or optimizing retrieval performance.

Quality

63%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./skills/similarity-search-patterns/SKILL.md

Quality

Content

43%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 well-structured and concise, but it lacks concrete, executable guidance — the instructions are generic boilerplate and the single external reference points to a missing file. Adding real patterns or restoring the referenced playbook would materially improve it.

Suggestions

Replace the abstract Instructions ('Apply relevant best practices and validate outcomes') with concrete, executable steps or a minimal code example for similarity search.

Create the referenced 'resources/implementation-playbook.md' (or fix the path) so the progressive-disclosure pointer resolves to a real file.

Add an explicit validation checkpoint (e.g., how to verify recall/latency after indexing) to turn the rough sequence into a real workflow.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's competence without explaining vector-DB concepts, but the generic Instructions boilerplate ('Apply relevant best practices and validate outcomes') could be trimmed.	4 / 5
Actionability	Guidance is high-level and abstract ('Apply relevant best practices', 'Provide actionable steps and verification') with no concrete code, commands, or specific patterns, and the referenced playbook for real examples does not exist.	2 / 5
Workflow Clarity	Only a generic rough sequence ('Clarify goals... Apply... validate outcomes') is present with poorly defined steps and no concrete validation checkpoints.	2 / 5
Progressive Disclosure	Sections are well-organized and a one-level-deep reference is clearly signaled, but the referenced 'resources/implementation-playbook.md' file is absent, breaking navigation.	3 / 5
	Total	11 / 20 Passed

Description

83%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 is strong: it clearly states the skill's purpose and provides explicit, natural trigger phrases for when to use it. It is mostly distinct from sibling skills and lists several concrete actions, with only minor synonym/coverage gaps.

Dimension	Reasoning	Score
Specificity	Names the domain ('similarity search with vector databases') plus several concrete actions ('building semantic search', 'implementing nearest neighbor queries', 'optimizing retrieval performance'), with only minor coverage gaps.	4 / 5
Completeness	Explicitly states both what it does ('Implement efficient similarity search with vector databases') and when to use it via a concrete 'Use when...' clause with multiple triggers.	5 / 5
Trigger Term Quality	Includes natural phrases users would say ('semantic search', 'nearest neighbor queries', 'retrieval performance') but misses common synonyms like 'vector search', 'embedding search', or 'find similar items'.	4 / 5
Distinctiveness Conflict Risk	The vector-database / similarity-search niche is mostly distinct with specific triggers, with only minor overlap risk against general RAG/retrieval skills.	4 / 5
	Total	17 / 20 Passed

Validation

100%

Warnings & errors only

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: rmyndharis/antigravity-skills
Path: skills/similarity-search-patterns/SKILL.md
Commit: 3eff4af

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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.