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Thegreatprabh

CODYNEX Engine

dna_plan

Predict full code-change impact for a natural-language request, identifying affected files, dependencies, and suggested tests across a Python codebase.

Instructions

Full change prediction for a natural-language request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNo
requestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

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 entire behavioral burden, and it discloses almost nothing: no indication of whether this is a read-only analysis or a mutating operation, no permission requirements, no cost/latency, and no note that a 'plan' may produce a large multi-file result. The word 'prediction' weakly implies a non-destructive analysis, but nothing is stated.

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?

It is a single front-loaded sentence with no filler, so nothing is wasted. However, the brevity is under-specification rather than efficiency: a meaningful statement about scope or output would have earned its place.

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 no output schema, no annotations, 0% schema coverage, and two undocumented parameters, the description should compensate but does not. It never says what a returned 'plan' contains or how 'project' scopes the prediction, so an agent lacks enough to invoke this confidently.

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

Parameters2/5

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

Schema description coverage is 0% and neither parameter is documented in the schema. The description hints that 'request' is natural-language free text, but says nothing about the optional 'project' parameter — its format, scope, or default — leaving half the inputs unexplained in both places.

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

Purpose3/5

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

The phrase 'Full change prediction' gives a rough verb+resource, but it is vague about what a 'prediction' actually yields and gives no distinction from the sibling dna_impact, which presumably also concerns change consequences. An agent cannot reliably tell from this sentence alone which of dna_plan/dna_impact/dna_map to pick.

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?

There is no when-to-use guidance, no prerequisites, and no reference to the sibling tools (dna_map, dna_impact, dna_decisions) that clearly occupy adjacent roles. The only implicit cue is 'natural-language request', which does not route the agent among alternatives.

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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