memory_answer

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

With only sparse annotations (readOnly false, destructive false), the description carries the full behavioral burden and does so thoroughly. It discloses the negative-retrieval flow, contradiction thresholds and policies, alternate scorer, retry and repair call limits, project requirement, citation offset semantics, and local-vs-remote distinction. There is 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 dense but every sentence carries operational information that an agent needs to invoke the tool correctly, and the purpose is front-loaded. No filler or redundant restatement of the tool name or schema is present.

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 complexity, absence of an output schema, and sparse annotations, the description covers the core algorithm, policy branches, call budgets, and project requirement well. It is slightly incomplete on concrete return-value structure, but the cited-answer behavior is described in enough detail for an agent to understand what it will receive.

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 for the 7 undocumented parameters, but it mentions only 'Explicit project required.' It does not explain query, type, limit, branch, followup, or max_bytes beyond what the raw schema already states; the citation-offset sentence is about output, not parameter meaning.

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 opening sentence states a specific verb and resource: 'Generate and verify a cited answer using the configured reasoning LLM.' It also differentiates from related recall tools by ending with 'Ordinary recall remains local,' so an agent can tell this tool apart from memory_recall and similar siblings.

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 clear context for when this tool is appropriate: it is the LLM-backed, cited-answer generator, in contrast to local recall. It does not name sibling tools explicitly or say 'use X instead when Y,' so it stops short of a full when/when-not structure, but the usage context is genuinely clear.

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