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type_flows

Trace type propagation across function call edges to reveal dominant types in data pipelines. Get typed data-flow edges, frequency rankings, and typed-to-untyped ratios. Helps reduce LLM token consumption and agentic search time.

Instructions

Trace how types flow through the codebase along call edges. Shows which types dominate the data pipeline and how they propagate between functions. Returns all typed data-flow edges, dominant types ranked by frequency, and counts of typed vs untyped call edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the tool returns three types of data: edges, dominant types, and counts. This gives insight into the tool's behavior without stating side effects, but is sufficient for a read-only analysis tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, each adding distinct information. Front-loaded with the main action. No redundancy or waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so description must explain return values. It covers edges, dominant types, and counts, but lacks detail on format or structure. Acceptable for a zero-parameter tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has zero parameters, so description cannot add param info. Baseline 4 applies. The description adds value by explaining output, which is relevant when no params are expected.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies a clear verb ('trace') and resource ('types flowing through codebase along call edges'). It distinguishes from siblings like 'trace_type' by focusing on global dominance analysis rather than tracing a single type's path.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., trace_type for specific type tracing). The description only states what it does, not context or exclusions.

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

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