suggest_metadata

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

With no annotations, the description fully covers behavioral traits: read-only, never edits YAML, requires embeddings for semantic fields, and explains the optional context object for what-if analysis. It mentions the output includes specific fields, enhancing transparency. No contradictions.

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 three sentences, each adding distinct value: purpose, usage, and behavioral nuance. It is front-loaded with the core action and returns list, no redundant or vague statements. Every sentence earns its place.

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 complexity (knowledge-graph analysis), the description covers purpose, usage, behavioral traits, and a list of return fields despite no output schema. It notes mode-dependent availability. Slightly lacking detail on error cases, but still largely complete for an AI agent.

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 baseline is 3. The description adds value by explaining the context object's purpose ('test metadata overrides without changing the note') and summarizing the returned fields, which goes beyond the schema definitions. This justifies a 4.

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 identifies the tool's action (analyze and propose knowledge-graph metadata) and the resource (one note). It distinguishes from sibling tools by emphasizing it is for analysis and suggestion, not modification. The explicit usage guidance before write_file further clarifies its unique role.

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 explicit when-to-use instructions: before write_file for classification help or to audit an existing note. It states it is read-only and never edits YAML, but does not specify when not to use it or list explicit alternatives. Sibling tool names are contextually available but not referenced.

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