hebbrix_ask

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

Beyond the read-only, idempotent, non-destructive annotations, the description discloses that the tool synthesizes answers with an LLM, cites the memory ids used, inherits the safety envelope of hebbrix_search, and fails closed with no citations if reasoning or evidence receipt is unavailable. This is substantial behavioral context that annotations alone do not 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 front-loaded with a concise one-sentence summary, followed by a clear example, alternatives, and failure mode. The inline return JSON is somewhat redundant given the output schema, but the overall structure is scannable and each sentence earns its place.

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?

The description covers purpose, usage, return shape, and failure behavior well, but the unexplained collection_id and include_graph parameters are a real gap for an agent deciding how to invoke the tool. The output schema mitigates return-value ambiguity, but parameter-level guidance is still missing.

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 input schema has three parameters but 0% description coverage, and the tool description does not explain collection_id or include_graph at all. It only indirectly implies what the question parameter should contain through the natural-language example, which is insufficient for correct invocation.

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 verb ('Answer'), the resource ('a natural-language question from memory'), and the key constraint ('in ONE call'). It explicitly differentiates itself from sibling tools by naming the orchestration it replaces (hebbrix_search + hebbrix_graph_query + profile), so an agent can easily tell what it does.

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 provides an explicit example of when to use the tool ('who works with me on Atlas and what did we decide?') and names the alternative composition it avoids. It does not include a 'when not to use' clause, but the substitution guidance is direct and unambiguous.

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