marrow_ask

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

No annotations are provided, so the description carries the burden. It commits to returning 'direct answer + supporting evidence' and strongly implies a read-only operation via 'Query'. While it doesn't explicitly state 'does not modify data', the language is unambiguous for an advisory tool.

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?

Two concise sentences with the action verb front-loaded ('Query the collective hive'). Every clause adds relevant information—what to ask, when to use, and what to expect in return—with no fluff.

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 single-parameter query tool with no output schema and no annotations, the description fully covers the required context: this is a non-mutating advisory query that returns an answer and evidence. The simplicity of the tool means no further detail is needed.

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 coverage is 100%, so the baseline is 3. The description adds value beyond the schema by giving concrete examples of what the query can contain ('failure patterns, what worked, what broke, recommendation'), which helps the agent formulate a proper query.

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 'Query' and identifies a clear resource ('collective hive'), with explicit examples of what can be asked (failure patterns, what worked, what broke, recommendations). This distinguishes it from sibling tools like marrow_think or marrow_digest, which focus on different operations.

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 states when to use the tool: 'before acting' and for getting recommendations or asking about decision history. It does not explicitly name alternatives or exclusion cases, but the context is clear enough for an agent to select it over memory-management or key-management siblings.

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