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export_to_qdrant

Export skills to Qdrant vector database for high-performance search and native payload filtering. Transforms source types into AI-ready skills and RAG knowledge.

Instructions

Export skill to Qdrant vector database format. Qdrant is a modern vector database with native payload filtering and high-performance search, serving 100K+ users.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skill_dirYes
output_dirNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavioral traits, but it only describes Qdrant's general features (filtering, performance) without specifying any tool behavior such as idempotency, overwrite policy, authorization needs, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise with two sentences. The first sentence captures the purpose directly. The second sentence provides background about Qdrant but is not strictly necessary for tool invocation, making it slightly wasteful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters, no annotations, and an output schema available, the description should clarify input expectations and behavior. It fails to address prerequisites, return format, or edge cases, leaving significant gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not explain what 'skill_dir' or 'output_dir' represent. The agent is given no semantic context beyond the parameter names and types, which is insufficient for correct usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Export skill to Qdrant vector database format') and the target resource. However, it does not differentiate from sibling export tools (e.g., export_to_chroma, export_to_faiss) which could confuse an agent selecting among them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus its alternatives. There is no mention of prerequisites, contexts, or exclusions, leaving the agent to rely solely on the name for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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