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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, covering safety. The description adds context that results are scoped to 'the user can access' (permission-filtered) and that it returns graph metadata needed for graphId parameters in other tools, which is useful behavioral information beyond the annotations.

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 two sentences and front-loaded with the core purpose, followed by usage guidance and downstream value. No unnecessary words or restatements, 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?

For a simple listing tool with one optional parameter, rich annotations, and no output schema, the description covers purpose, content scope, and usage timing. It is complete for an AI agent to select and invoke the tool correctly.

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 input schema covers the single optional userId parameter with 100% description coverage, explaining automatic authentication for non-trial users. The tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

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 and resource: 'List all expert knowledge graphs the user can access', and details the returned fields (IDs, descriptions, authors, sectors, signal counts, topic coverage). It distinguishes from siblings by framing itself as the session-first discovery tool before searching, which separates it from search_graph and deep_research_topic.

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 explicitly says 'Use FIRST in any session to discover available sources before searching', offering clear when-to-use guidance. It does not name alternative tools directly, but the 'before searching' cue implies its role relative to search-related siblings. No when-not-to-use exclusions are provided, so it stops short of a 5.

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