Extract (subject, predicate, object) triplets from text to identify relationships and build structured knowledge graphs. Turns unstructured text into actionable relational data.
Extract relations and (subject, predicate, object) triplets from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Input text to extract relations from |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the operation without mentioning read-only nature, output format, or any side effects. For a tool that extracts relations, the read-only assumption is implied but not explicitly stated, leaving an agent without complete behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant phrasing. Every word contributes to conveying the purpose, making it highly concise and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description is adequate for basic use. It clarifies the core operation but does not specify the output format (e.g., list of triplets) or any constraints. Since no output schema exists, describing the return shape would improve completeness, but the current description is sufficient for straightforward extraction.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for the single parameter 'text' is already descriptive ('Input text to extract relations from'), achieving 100% coverage. The description's mention of 'from text' adds no new meaning beyond what the schema provides, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('extract') and resource ('relations and (subject, predicate, object) triplets') from text, making the tool's function immediately clear. It also distinguishes it from sibling 'extract_entities', which focuses on entities rather than relations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when relations need to be extracted from text, but provides no explicit when-to-use guidance or exclusions. It does not mention alternative tools like 'extract_entities' or clarify when this tool should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.