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Validate Prompt

validate_prompt

Validate prompt assumptions against target registry facts to identify mismatches before migration.

Instructions

Statically validate prompt assumptions against target registry facts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
targetYes
source_pathNo
target_endpointNo
target_platformNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • addedInput schema / properties / target_endpoint
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null
      +}
  2. First observedv1.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It says the validation is 'static' but does not explain side effects, failure modes, what happens when assumptions conflict with registry facts, or whether this is a read-only operation. The description provides only a high-level intent, not enough behavioral transparency for a tool with no annotation safety hints.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no filler. It is compact and readable. It loses a point because 'statically validate' is slightly jargon-heavy and the sentence carries insufficient detail, but as a standalone statement it is appropriately sized.

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 five parameters, zero annotation coverage, and no parameter documentation in the schema. Although an output schema exists, the description still fails to convey what inputs are expected beyond the two required ones, when to use the tool, or what the validation guarantees. This is inadequate for correct invocation in an agentic context.

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%, so the description must compensate by explaining the five parameters. It only hints at 'prompt assumptions' and 'target registry facts,' which loosely maps to prompt and target, but it never explains source_path, target_endpoint, or target_platform. The optional parameters remain completely undocumented, leaving an agent without enough meaning to populate them correctly.

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?

The description states a clear action ('validate'), a specific object ('prompt assumptions'), and a reference point ('target registry facts'). The qualifier 'statically' adds mode-of-operation detail. It does not explicitly name sibling tools, but the action is specific enough to separate it from broader analysis tools like analyze_prompt.

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 given about when to choose this tool over siblings such as analyze_prompt, validate_evidence_review, or run_migration_eval. There are no exclusions, prerequisites, or alternative conditions. Usage context is only weakly implied by the verb 'validate'.

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