CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

chromadb

Provides Chroma Python client patterns — collection creation and configuration, add/upsert/query, metadata and document filtering syntax, and embedding function integration. Use when the user asks to "set up ChromaDB", "create a Chroma collection", "add embeddings to ChromaDB", "query ChromaDB", "search vectors", "semantic search with ChromaDB", "filter ChromaDB results", "ChromaDB metadata filtering", "configure Chroma", "use ChromaDB persistent client", "delete from ChromaDB", or when writing any code that interacts with the chromadb Python package. Does not cover the JavaScript client, Chroma Cloud, choosing an embedding model, or general RAG architecture.

72

Quality

90%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

80%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.

A strong reference-style body: executable examples throughout, high-value gotcha documentation, and clean two-file progressive disclosure. The main gap is the absence of validation checkpoints around destructive and batch operations, which the rubric explicitly caps, plus minor duplication with the reference files.

Suggestions

Add validation guidance for destructive and batch operations: e.g., preview matching records with collection.get(where=...) and compare collection.count() before/after collection.delete(...), mirroring the existing verify-count hint for the silent add failure.

Trim the opening sentence (it restates the frontmatter description) and consider collapsing the ten-row operator table to the handful of common operators, pointing to references/api-reference.md for the complete set that already exists there.

Fold a brief 'verify after write' note into the batch-ingestion guidance (e.g., check count() after each chunk or at the end), since references/patterns.md currently shows chunking without any post-write verification.

DimensionReasoningScore

Conciseness

The body is efficient and focused on non-obvious behavior (silent duplicate-ID skips, nested vs. flat result lists, include-always-present keys, CHROMA_ env-var precedence, legacy embedding-function fallback) with no concept-explanation padding. Minor trims remain: the opening sentence duplicates the frontmatter description, and the ten-operator filter table overlaps the "Filter Operators (Complete Reference)" in references/api-reference.md.

4 / 5

Actionability

Every section contains complete, copy-paste-ready Python with concrete values (client init, add/upsert/query/get, filters, embedding functions), plus an operator table with per-operator examples and a symptom/cause/fix table for common errors.

5 / 5

Workflow Clarity

Operations are presented in a logical sequence (client → collections → add → query → filter → update/delete → errors) and the Common Errors table supplies recovery guidance, but destructive and batch operations — delete_collection, delete(where=...), bulk add/upsert — have no explicit validation checkpoints (e.g., preview with get() or verify count() before/after), which per the rubric caps this dimension at 3.

3 / 5

Progressive Disclosure

Both referenced files (references/api-reference.md, references/patterns.md) exist, are one level deep with their own tables of contents and no further nesting, and are clearly signaled both at point-of-use ("For complete filter operator details … consult references/api-reference.md") and in a final annotated Reference Files list. The basics-inline / details-external split is appropriate.

5 / 5

Total

17

/

20

Passed

Description

96%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.

An exemplary description: third-person voice, concrete capability list, an explicit "Use when" clause with natural trigger phrases, and clear boundary exclusions. The only weakness is a couple of unqualified generic triggers that slightly raise conflict risk with other vector-database skills.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "collection creation and configuration, add/upsert/query, metadata and document filtering syntax, and embedding function integration" — giving comprehensive coverage of the Chroma client surface rather than a few actions with gaps.

5 / 5

Completeness

It explicitly answers both questions: the "what" ("Provides Chroma Python client patterns — …") and the "when" ("Use when the user asks to …") with a list of concrete quoted trigger phrases, matching the anchor-5 pattern exactly.

5 / 5

Trigger Term Quality

Trigger phrases are natural user phrasings with synonyms: "set up ChromaDB", "create a Chroma collection", "add embeddings to ChromaDB", "query ChromaDB", "search vectors", "semantic search with ChromaDB", "filter ChromaDB results", "delete from ChromaDB", plus the package name "chromadb Python package" covering technical variants.

5 / 5

Distinctiveness Conflict Risk

The niche is clear and exclusions are explicit ("Does not cover the JavaScript client, Chroma Cloud, choosing an embedding model, or general RAG architecture"), but unqualified generic triggers like "search vectors" and "semantic search" could fire for other vector-store skills, leaving minor overlap risk rather than minimal.

4 / 5

Total

19

/

20

Passed

Validation

100%

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

provectus/awos-recruitment

Path

.claude/skills/chromadb/SKILL.md

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.