Skip to main content
Glama

robot_chain

Execute multiple ROBOT ontology commands as a pipeline, passing objects in memory for efficiency without writing intermediate files.

Instructions

Execute a chain of ROBOT commands in a single process.

Ontology objects pass in-memory between steps — much more efficient than writing intermediate files. Only the first step typically needs an input key and only the last step needs an output key.

Each step is a dict with:

  • command: the ROBOT command name (e.g. "merge", "reason")

  • All other keys are command arguments. Use the long flag name without leading dashes, with hyphens replaced by underscores.

Argument mapping rules:

  • Underscores become hyphens: ontology_iri--ontology-iri

  • list values repeat the flag: {"input": ["a.owl", "b.owl"]}--input a.owl --input b.owl

  • bool values become "true" / "false" strings

  • str / int values become a single flag-value pair

Example steps::

[
    {"command": "merge", "input": ["edit.owl", "base.owl"]},
    {"command": "reason", "reasoner": "ELK"},
    {"command": "annotate", "ontology_iri": "https://example.org/my.owl"},
    {"command": "convert", "format": "ofn", "output": "result.owl"}
]

Tip: to discover available flags for a command, pass "help": true in a step, e.g. [{"command": "merge", "help": true}].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stepsYes
working_directoryNo
catalogNo
prefixesNo
add_prefixNo
noprefixesNo
verboseNo
strictNo
xml_entitiesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It explains in-memory passing, argument mapping rules, and provides examples. It does not mention error handling or side effects, but the behavior is well-covered.

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?

The description is concise, well-structured with bullet points and code blocks. It front-loads the purpose and provides necessary details without unnecessary text.

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 9 parameters and an output schema, the description covers the main functionality and steps usage. It lacks explanations for some optional parameters, but they are straightforward. Overall, it is fairly complete.

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 coverage is 0%, so description must compensate. It thoroughly explains the 'steps' parameter structure and argument mapping. Other parameters like working_directory and catalog are not individually explained, but they are standard and less critical.

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 it executes a chain of ROBOT commands in a single process, distinguishing it from sibling tools which are single commands. It specifies the verb and resource precisely.

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?

Provides guidance on when to use (e.g., chaining multiple commands) and notes that only first step needs input, last needs output. It also suggests using 'help':true to discover flags. However, it does not explicitly state when not to use (e.g., for single commands).

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/musen-lab/robot-tool-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server