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run_xml_verification

Run a quality verification using an XML specification file with per-condition filters and default values, providing a summary of errors.

Instructions

Run a ProSuite quality verification directly from the loaded XML spec file.

Unlike run_verification, this tool sends the XML spec to the ProSuite service as-is, without decomposing it into individual conditions and datasets. This preserves per-condition dataset filters, default scalar values, and all other spec details exactly as configured.

Use search_spec (with empty query) to discover available specification_name values and workspace_id keys that need to be replaced.

Args: specification_name: Name of the QualitySpecification element inside the XML file to run (e.g. 'Copy of DATA_OSM_10_Demo'). data_source_replacements: Maps each workspace_id in the XML to the actual workspace path on the ProSuite server. Example: [{"workspace_id": "DATA_OSM", "workspace_path": "C:/data/osm.sde"}] output_dir: Optional server-side directory for Issues.gdb and HTML report. envelope: Optional spatial filter {x_min, y_min, x_max, y_max}.

Returns a summary with status, total_errors, and per-condition breakdown. Requires PROSUITE_SPEC_PATH to be configured.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
envelopeNo
output_dirNo
specification_nameYes
data_source_replacementsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations present, so description carries full burden. It explains that the tool preserves per-condition filters and default scalar values, and that it requires PROSUITE_SPEC_PATH to be configured. However, it does not detail potential errors or side effects (e.g., what happens on failure). Output schema exists to cover return structure.

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 well-structured with a summary, comparison, usage hint, and parameter list. It is concise but not overly brief; every sentence adds value. Could be slightly more front-loaded, but overall efficient.

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

Completeness4/5

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

Given 4 parameters, no annotations, and an output schema, the description covers the tool's behavior, prerequisites, and parameter details adequately. It could mention error handling or limitations, but it is sufficient for an AI agent to use correctly.

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?

Schema description coverage is 0%, so description must compensate. It provides detailed explanations for each parameter in the Args section, including a concrete JSON example for 'data_source_replacements'. This adds significant meaning beyond the schema.

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 clearly states the tool's purpose: to run a quality verification directly from the loaded XML spec file. It uses specific verbs ('Run') and resource ('ProSuite quality verification from XML spec') and distinguishes from sibling 'run_verification' by explaining how it processes the spec.

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

Usage Guidelines5/5

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

Explicitly contrasts with sibling tool 'run_verification' and advises using 'search_spec' to discover spec names and workspace IDs. This provides clear when-to-use and when-not-to-use guidance, as well as prerequisites.

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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