extract_entities

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

With no annotations, the description bears full responsibility. It explains the extraction methods (rule-based + optional LLM) and auto-save behavior, but lacks details on potential side effects, performance implications, or output format.

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 concise, with two paragraphs that efficiently convey the tool's action and use. It is front-loaded and every sentence adds value, though minor trimming is possible.

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?

The description covers entity types and basic behavior, but lacks details about return values (no output schema) and does not mention edge cases or error handling. For a tool with 3 parameters, it is adequate but not thorough.

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%, so the schema already documents all parameters. The description adds context about entity types and overall purpose, but doesn't significantly enhance parameter understanding beyond the schema.

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 extracts named entities from raw text, listing specific entity types (PERSON, PROJECT, TECH, etc.). It effectively distinguishes itself from siblings, none of which offer similar 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 a clear use case: auto-enrich session context. While it doesn't explicitly mention when not to use or alternatives, the sibling tools are mostly unrelated, making the guidance sufficient.

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