robot-tool-mcp

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robot_repair

Repairs ontology problems by updating deprecated class references, merging duplicate axiom annotations, and fixing invalid references.

Instructions

Fix common ontology problems.

Repairs include: updating references to deprecated classes (replacing them with their replacements), merging duplicate axiom annotations, and fixing invalid references.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "robot_repair"
  }
}

Input Schema

Name	Required	Description	Default
`input`	No
`output`	No
`invalid_references`	No
`annotation_property`	No
`merge_axiom_annotations`	No
`working_directory`	No
`catalog`	No
`prefixes`	No
`add_prefix`	No
`noprefixes`	No
`verbose`	No
`strict`	No
`xml_entities`	No
`extra_args`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.2.2May 29, 2026

TDQS

B3.2/5.0

Behavior2/5

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

With no annotations, the description must fully disclose behavior. It mentions types of repairs but fails to state whether the tool modifies the ontology in place, requires write permissions, or has side effects. The agent is left guessing about destructive potential and operational context.

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 concise with two sentences, no redundant text. However, it could be better structured with bullet points or explicit mapping to parameters without increasing length significantly. It front-loads the general purpose but lacks detail.

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?

Given the tool's complexity (14 parameters, no schema descriptions, no annotations) and presence of an output schema, the description is too sparse. It fails to provide sufficient context for an agent to correctly invoke the tool, especially regarding parameter usage and output interpretation.

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 should explain parameters. It only references 'invalid_references' and 'merge_axiom_annotations' indirectly via the listed repairs, leaving 12 other parameters (e.g., input, output, catalog, prefixes) completely unexplained. The description adds minimal value beyond parameter names.

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 that the tool fixes common ontology problems and lists three specific types of repairs: updating deprecated class references, merging duplicate axiom annotations, and fixing invalid references. It effectively distinguishes itself from sibling tools which perform other operations like annotation, conversion, or filtering.

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

Usage Guidelines3/5

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

The description implies usage for ontology repair tasks but does not explicitly state when to use this tool over alternatives like robot_validate_profile or robot_verify. No context on prerequisites or exclusions is provided, leaving the agent with only implied guidance.

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