extract_entities

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

No annotations provided. Description hints at caching via 'force_regenerate' parameter and mentions AI usage, but does not disclose read/write behavior, side effects, or rate limits. Behavioral traits are partially covered.

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?

Two sentences, front-loaded with main action, efficient and no unnecessary words.

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?

No output schema exists. Description mentions return fields (type, confidence, context) but omits structure details (e.g., nested objects, arrays). For a complex AI extraction tool, more output specification is needed.

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 coverage is 100%, so baseline is 3. Description adds general context about entity types and output structure but does not add meaningful parameter-specific semantics beyond what the schema already provides.

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?

Description clearly states it extracts named entities from C64 documents, lists specific entity categories (hardware, memory addresses, etc.), and mentions output fields (type, confidence, context). It distinguishes from siblings like extract_entities_bulk and extract_entity_relationships.

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?

Notes 'Requires LLM configuration' but does not explicitly state when to use this tool vs. alternatives (e.g., bulk extraction, queueing). Lacks explicit 'when not to use' or comparison with sibling tools.

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