ontomics

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. It describes what the tool does (traces type flows, shows dominant types, returns edges and counts) but doesn't cover aspects like performance characteristics, error handling, or whether it requires specific codebase states. It adds useful context about output structure but lacks details on limitations or side effects.

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 efficiently structured in three sentences that each add value: first states the core action, second explains what it reveals, third details the return format. There's no redundant information, and it's front-loaded with the main purpose.

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 (analyzing type flows in codebases) and lack of annotations/output schema, the description is moderately complete. It explains the tool's purpose and output structure but doesn't cover how results are formatted, potential limitations, or integration with other tools. For a zero-parameter analysis tool, this is adequate but could benefit from more behavioral context.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to compensate for parameter gaps, and it appropriately focuses on what the tool does rather than input details, meeting the baseline for zero-parameter tools.

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 with specific verbs ('trace', 'shows', 'returns') and resources ('types flow through the codebase', 'call edges', 'data pipeline', 'functions'). It distinguishes from siblings like 'trace_concept' by focusing on type flows rather than concept tracing, and from 'describe_logic' by analyzing data flow patterns rather than describing logic.

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 implies usage for analyzing type propagation in codebases, suggesting it's for understanding data flow patterns. However, it doesn't explicitly state when to use this tool versus alternatives like 'trace_concept' (for concept flows) or 'describe_logic' (for logic description), nor does it provide exclusions or prerequisites for use.

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