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validate_plan

Read-onlyIdempotent

Validate a multi-step geoprocessing plan before execution: catch invalid operations, missing arguments, mis-ordered references, and CRS mismatches. Returns actionable errors without running anything.

Instructions

Statically validate a multi-step geoprocessing plan BEFORE running anything.

Write the plan as steps in execution order; each step has a unique id, an operation name from list_operations, and its arguments. Use "$step_id" as an argument value to consume the output dataset of an earlier step. Checks: operations exist and are installed, arguments complete and well-typed, references resolve backwards (mis-ordered steps are rejected), input files exist, outputs don't collide, and CRS flow is simulated end-to-end from the real input files. Returns machine-actionable errors/warnings/notes plus the simulated output CRS per step. Nothing is executed and nothing is written.

Example plan: {"goal": "wells at risk", "steps": [ {"id": "buf", "operation": "buffer_layer", "arguments": {"input_path": "wells.gpkg", "distance_meters": 300, "output_path": "buf.parquet"}}, {"id": "cut", "operation": "clip_layer", "arguments": {"input_path": "$buf", "mask_path": "zone.gpkg", "output_path": "risk.parquet"}}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description details exactly what validation covers: operation existence, argument completeness/typing, backward reference resolution, file existence, output collision checks, and CRS flow. It also states the return shape (errors/warnings/notes plus simulated CRS) and explicitly promises no side effects: 'Nothing is executed and nothing is written.'

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 longer than average, but it earns the length by covering validation semantics, plan structure, reference syntax, and return behavior. The example plan is helpful. A small amount of redundancy exists ('BEFORE running anything' vs. 'Nothing is executed'), but overall the structure is logical and front-loaded.

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?

For a validation tool with one complex nested parameter and no need to document return values thanks to the output schema, this description is complete. It tells the agent what the input must look like, what checks will be performed, what the result contains, and that the tool has no side effects. Nothing essential is missing.

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

Parameters5/5

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

The single `plan` parameter is thoroughly explained: steps in execution order, unique ids, operation names from list_operations, and the crucial `$step_id` reference syntax for consuming earlier outputs. The description even provides a concrete example plan. This compensates fully for the 0% schema description coverage at the top level.

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?

The description opens with a precise verb and object: 'Statically validate a multi-step geoprocessing plan BEFORE running anything.' It clearly distinguishes this from execution-oriented siblings like execute_plan and run_operation, and the details about validation checks reinforce what the tool is for.

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?

The description makes the usage context explicit: validate before executing, and use operation names from list_operations. It doesn't explicitly name execute_plan as the follow-up tool, but the 'BEFORE running anything' framing and the contrast with execution-oriented sibling tools give an agent clear guidance on when this tool applies.

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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