kg_query_context

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It tells what the tool does but does not reveal any behavioral traits such as read-only nature, output format, limitations, or side effects. For a query-like tool, it should at least indicate that it does not modify data or describe what the result includes.

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 two sentences long, front-loaded with the core action, and contains no filler. Every sentence earns its place: the first explains what it does, and the second gives a usage context.

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 tool is simple (one required parameter) and the description covers the purpose and usage. However, with no output schema and no annotations, the description should provide more context about what the tool returns (e.g., a list of related nodes or a graph) and any behavior assumptions. It is adequate but leaves gaps.

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 schema already provides 100% coverage for the single parameter 'topic' with a clear description and examples. The tool description adds no additional meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 what the tool does: 'Reconstructs context around a specific topic by analyzing related knowledge nodes.' It uses a specific verb ('reconstructs') and resource ('context around a topic'), which is clear and distinct. However, it does not explicitly differentiate itself from sibling tools like kg_get_relevant_context, which may serve a similar purpose.

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 says 'Use to understand the full context and background of a particular subject area,' which provides clear guidance on when to use this tool. It lacks explicit exclusions or alternatives, but the stated use-case is specific and helpful.

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