analyze_cognitive_topology

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

No annotations are provided, so the description carries the full burden. It clearly describes the nature of the tool (analysis, generating a portrait) and its outputs, but it does not explicitly state whether this operation is non-mutating or mention any side effects, performance implications, or data access constraints. The verb 'Analyze' and 'Generates' imply safety, but the description could be more explicit.

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 compact (two sentences) and front-loaded with the primary action. It efficiently communicates the core purpose and the key output elements without any fluff. Every clause adds informational value.

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 that there is no output schema, the description reasonably details the returned 'cognitive portrait' and its components. It also implies an optional parameter through the schema. It does not mention example use cases or potential caveats, but for a read-only analysis tool, this is largely sufficient.

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 schema covers 100% of the parameter ('domain') with its own description, so the baseline is 3. The tool description does not add any additional semantic meaning about how 'domain' affects the analysis, but the schema already provides sufficient context.

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 uses a specific verb ('Analyze') and a clear resource ('knowledge graph'), and it enumerates concrete outputs ('knowledge islands, bridge concepts, dense/sparse regions') that differentiate it from sibling tools like discover_connections or detect_blindspots. The purpose is unmistakable and distinct.

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 implies usage for obtaining a high-level structural overview and connectivity recommendations, but it does not explicitly state when to use this tool over siblings or provide exclusions. The context is clear from the output described, but there is no direct guidance on choosing alternatives.

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