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design_validate_plan

Validate candidate DesignPlan JSON against schema and cross-references before execution, catching errors that would block plan execution without an Altium round-trip.

Instructions

Validate a candidate DesignPlan JSON against the schema + cross-check.

Run this before design_execute_plan to catch schema problems and cross-references that the executor will reject. Cheap; no Altium round-trip.

Args: plan_json: Either a JSON string of the DesignPlan, or the DesignPlan as a JSON object/dict. The MCP framework auto-deserializes JSON-object literals to dicts before the tool sees them, so both shapes are accepted.

Returns: {"ok": True, "summary": "..."} on success, or {"ok": False, "errors": [...]} listing the specific problems. The planner can read these and revise.

Input Schema

NameRequiredDescriptionDefault
plan_jsonYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A4.5/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden and mostly meets it: 'cheap; no Altium round-trip' signals no side effects and no external mutation, and the exact response envelope for both success and failure is given. What is missing is an explicit statement that the call is non-mutating/read-only in all cases and whether it logs or caches anything.

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?

Front-loaded with the purpose and the sequencing instruction, then a compact Args/Returns block. Every sentence adds information; the auto-deserialization note is short and prevents a real input-shape mistake.

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

Completeness5/5

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

Covers purpose, prerequisite ordering, accepted input shapes, success/failure return shapes, and cost characteristics. Although an output schema exists, the description's short return summary is complementary rather than redundant, and nothing an agent needs to invoke it correctly is missing.

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?

Schema description coverage is 0% and the schema only offers an anyOf of string/object, so the description does real work: it explains that both a JSON string and an already-deserialized dict are accepted and why. It does not describe what a well-formed DesignPlan must contain, which the agent must learn elsewhere.

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?

States a specific verb+object: validate a candidate DesignPlan JSON against the schema plus cross-references. It is clearly distinct from design_execute_plan (which it precedes) and from design_validate, since the object is a plan document rather than a live design.

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

Usage Guidelines4/5

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

Explicitly says to run it before design_execute_plan and why (to catch problems the executor will reject). That routes the agent correctly against the main alternative, but there is no stated when-not-to-use or cost-free alternative for a quick field-only check.

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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