knot

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

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits: it states 'Read-only graph traversal with no side effects', describes the return format ('Returns Markdown grouped by relationship type with exact file paths and line numbers'), and specifies supported languages ('Supports Java, Kotlin, and TypeScript codebases'). The only minor gap is lack of information about rate limits or performance characteristics.

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 well-structured and front-loaded with purpose, followed by usage guidelines, behavioral information, parameter guidance, and language support. Every sentence earns its place by adding distinct value: no repetition, no fluff, and clear sectioning with headings like 'Usage:', 'Behaviour & Return:', and 'Parameter guidance:'.

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 2-parameter tool with no annotations and no output schema, the description provides excellent coverage of purpose, usage, behavior, and parameters. It explains what the tool returns (Markdown grouped by relationship type) despite lacking an output schema. The only minor gap is not explicitly mentioning error conditions or edge cases, but overall it's highly complete for the tool's complexity.

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?

With 100% schema description coverage, the baseline is 3, but the description adds significant value beyond the schema. It explains that 'entity_name' supports 'exact names or signature fragments' with examples, clarifies that 'repo_name' filters 'to the specific codebase being analyzed', and emphasizes that including repo_name is 'HIGHLY RECOMMENDED' to avoid mixed results. This provides crucial context not in the schema alone.

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 tool's purpose: 'Read-only reverse dependency lookup' that 'finds all code that references, calls, extends, or implements a specific entity' and 'answers who uses this code?'. It explicitly distinguishes from sibling tools by stating it 'differs from search tools by providing exact dependency tracking' and contrasts with 'search_hybrid_context' for semantic feature discovery.

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 explicit guidance on when to use ('for impact analysis before refactoring or to detect dead code') and when NOT to use ('Do NOT use this for semantic feature discovery—use search_hybrid_context instead'). It also includes critical usage advice about including signature fragments for common method names to prevent irrelevant results.

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