concept_cover

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

No annotations are provided, so the description must carry the full burden of disclosing behavior. The description does explain what the tool outputs (chunking, memory coverage, top-k) and adds theoretical context (working-memory chunking, Miller 1956). However, it does not explicitly state whether the operation is read-only, whether it has side effects, or how the output is presented. The verb 'Show' implies non-destructive behavior, but this is not made 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 a single, front-loaded sentence that efficiently conveys the tool's purpose and output. The parenthetical reference to Miller (1956) adds relevant theoretical context without being verbose. Every part of the sentence is informative and there is no filler.

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 2-parameter 'show' tool without an output schema, the description provides a good level of context: it explains the core process (chunking, memory coverage, top-k) and the specific domain (Chinese questions). It does not detail the exact output format or any prerequisites, but given the tool's apparent simplicity, it is reasonably complete. The absence of an output schema is mitigated by the clear description of what is shown.

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 0%, so the description must compensate. It does add meaning: 'query' is described as a multi-concept Chinese question, and 'top_k' relates to the 'final top-k'. However, it does not explain the expected format of the query, the default value for top_k, or how these parameters influence the chunking process. The description provides partial meaning but leaves significant gaps.

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 function: it shows how a multi-concept Chinese question is split into chunks, which memories cover each chunk, and the final top-k. This is a specific verb ('Show') plus a resource ('multi-concept Chinese question') and distinguishes the tool from siblings like 'working_set' and 'memory_map' by focusing on the chunking and memory coverage visualization.

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 understanding the memory retrieval and chunking process for a multi-concept Chinese question, but it does not explicitly state when to use this tool vs alternatives or provide exclusions. There is no mention of prerequisites or conditions where this tool is preferred over similar tools like 'working_set' or 'explain_memory'.

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