extract_keywords

Does 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 mentions the TF-IDF algorithm, which hints at computational behavior, but doesn't cover critical aspects like performance (e.g., processing time for large notes), error handling (e.g., what happens if the path is invalid), or output format (e.g., list of keywords with scores). This leaves significant gaps for an agent to understand how the tool behaves.

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, efficient sentence: 'Extract keywords from note content using TF-IDF algorithm.' It is front-loaded with the core purpose and includes the method, with zero wasted words. This makes it easy for an agent to parse quickly.

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 complexity of keyword extraction (involving algorithms and data processing), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the output looks like (e.g., a list of keywords, possibly with scores), error conditions, or behavioral traits like rate limits. This leaves the agent with insufficient context for reliable use.

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?

Schema description coverage is 100%, with both parameters ('path' and 'maxKeywords') well-documented in the schema. The description adds no additional parameter semantics beyond what the schema provides, such as explaining the note format expected at the path or how TF-IDF influences keyword selection. Baseline score of 3 is appropriate since the schema does the heavy lifting.

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 clearly states the tool's purpose: 'Extract keywords from note content using TF-IDF algorithm.' It specifies the verb ('extract'), resource ('keywords from note content'), and method ('TF-IDF algorithm'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'suggest_tags' or 'analyze_note_relationships', which might offer overlapping functionality.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as requiring an existing note at the specified path, or compare it to similar tools like 'suggest_tags' or 'analyze_note_relationships' for keyword extraction. Usage is implied by the purpose but lacks explicit context or exclusions.

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