query_knowledge

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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it succeeds: it states retrieval type (BM25), constraints (no web, no LLM), performance expectations (free and fast), result properties (current, dated, rank-ordered), and return shape (JSON with cards and coverage). This gives an agent an accurate model of what will happen when invoked.

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?

Although the description is longer than typical, it is tightly organized into purpose, usage routing, scope exclusions, and argument definitions. Every section earns its place because it prevents a specific misuse, and the core purpose is front-loaded in the first line.

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, the lack of annotations, and the absence of a formal output schema, the description is complete. It covers what the tool does, when to prefer alternatives, what inputs it accepts, what it returns, and what it explicitly does not cover — nothing an agent needs to call it correctly is 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?

Schema coverage is 0%, so the description fully compensates. It defines `question` as 'what to look up' and `topic` as an optional filter with an explicit list of known slugs. This is considerably more informative than the bare schema, which provides no descriptions and no enums.

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 opens with a specific verb and resource — 'Search the AmiticIA knowledge base' — and immediately distinguishes itself from the sibling `research` tool by naming the alternative and its different purpose. An agent can tell exactly what this tool does and what it is not for.

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 explicit when-to-use guidance ('quick grounded read of what has already been accumulated') and when-not-to-use guidance ('use `research` when you need live web evidence and a synthesized answer'). It further provides SDK-first routing and clear exclusions for general architecture questions and library/API docs.

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