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

The description adds essential behavioral context (free-text matching, relevance ranking, coverage limitation) beyond the annotations (readOnlyHint, idempotentHint, destructiveHint). No contradiction with 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 paragraphs; the first states the core purpose concisely, the second adds important usage notes. It is front-loaded and informative, though slightly verbose with the alternative-lens note.

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 presence of an output schema (not shown but inferred), the description does not need to detail return values. It covers purpose, usage, search behavior, and limitations, making it complete for a search tool with good annotations and schema coverage.

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 that the query is matched against principle title, definition, rationale, and cluster, which is more specific than the schema description alone.

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 ('search') on a defined resource ('principles'), clearly states the return fields (title, cluster, definition, rationale, implementation heuristics), and explicitly distinguishes from the sibling tool principles.list by usage context.

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 gives explicit when-to-use guidance ('when you have a specific topic in mind rather than wanting all principles'), suggests example queries, and notes a current limitation (only covers agentic principles) with an alternative for other lenses.

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