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

With no annotations, the description carries the full burden. It discloses that the tool performs retrieval (RAG) and returns multiple data types, confirming it is a read-only operation. It does not mention side effects, rate limits, or auth needs, but given the nature of a query tool, the description is sufficiently transparent beyond what schema/annotations provide.

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 concise sentences. The first sentence states the primary action and resource, the second lists return types, and the third provides usage guidance. No redundant or unnecessary information, and key points are front-loaded.

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 (RAG with multiple return types) and the presence of an output schema, the description adequately explains what the tool returns. It covers the retrieval method and expected outputs but could be more complete by mentioning potential limitations or error scenarios. Still, it provides sufficient context for an agent to use the tool effectively.

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?

Both parameters have schema descriptions (100% coverage) and are clear. The tool description adds no additional semantic value beyond the schema (e.g., no extra formatting or usage hints). Baseline score of 3 is appropriate since schema already documents parameters adequately.

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 states the tool's purpose: asking a natural-language question and receiving structured intelligence context from Tresslers Group dossiers via RAG. It lists specific return types (document chunks, source citations, etc.) and distinguishes from siblings which are more specialized (e.g., query_knowledge_graph for graph queries, read_dossier for single dossiers).

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 natural-language questions across dossiers and advises the LLM to synthesize returned context into an answer. However, it does not explicitly state when to use this tool versus its siblings (e.g., list_dossiers, read_dossier) or provide exclusion criteria, leaving the agent to infer appropriate contexts.

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