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dispersl_code_agent

Generates code files and full codebases from a prompt using agentic execution, enabling AI-driven software development and multi-agent orchestration.

Instructions

Generate code files and codebases based on a prompt using agentic execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mcpNo
modelNo
promptYes
contextNo
task_idNo
knowledgeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

C2.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. 'Agentic execution' is vague — it does not say whether files are written to disk, whether the task is long-running/async, what permissions or model configuration are needed, or what side effects occur. For a code-generation agent with a nested mcp config parameter, this leaves important behavior undisclosed.

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?

A single efficient sentence with no waste, and the core action is front-loaded. However, that brevity comes at the cost of under-specification rather than genuine conciseness.

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?

With 6 parameters including a nested object, no annotations, and no output schema, the description is far too thin to let an agent invoke this correctly. Critical details about inputs, execution model, and results are missing.

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

Parameters1/5

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

Six parameters at 0% schema description coverage, and the description only maps to 'prompt'. The purpose of mcp, model, context, task_id, and knowledge is unexplained in both the schema and the description, leaving half the API surface opaque.

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

Purpose4/5

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

States a specific verb (generate) and resource (code files and codebases) with the mechanism (agentic execution), which distinguishes it from sibling agents like dispersl_plan_agent and dispersl_testing_agent. It stops short of explicitly contrasting with those siblings, but the resource is clear.

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 versus the other dispersl_* agents (plan, testing, git, docs, chat) or when not to. An agent must infer the boundary purely from the tool name.

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