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coding_build_codegraph

Build a code graph from a natural language message and optional structured inputs to analyze or visualize code dependencies.

Instructions

Run the coding domain agent action build_codegraph.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageNo
inputsNo{}

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations, the description carries the full burden. It only mentions routing through a dispatcher with JWT/tenant/company scope, but does not disclose whether the tool has side effects, what it returns (beyond existence of output schema), or any other behavioral traits.

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

Conciseness3/5

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

The description is short and directly states the action, but it is not front-loaded with a clear summary. The single sentence explaining the action is followed by routing details and then the arg list, which is structurally adequate but could be more informative.

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

Completeness2/5

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

The tool has an output schema but the description does not reference what the tool returns or elaborate on the codegraph concept. Given the complexity and lack of annotations, the description leaves significant gaps about expected inputs and outputs.

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

Parameters3/5

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

The schema has 0% description coverage, so the description is the sole source of parameter meaning. It defines 'message' as 'Free-text objective for the action' and 'inputs' as 'Optional JSON string of structured inputs', which adds basic semantics but lacks detail about format or expected content.

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

Purpose2/5

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

The description states 'Run the coding domain agent action `build_codegraph`' which is nearly tautological with the tool name. It does not explain what building a codegraph accomplishes or how it differs from sibling tools like coding_chat or coding_explain_code.

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 is provided on when to use this tool versus alternatives. The description contains no conditions, exclusions, or references to other tools for comparison.

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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