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RISBridge MCP

by CodeMonk6

Create pipeline

ris_create_pipeline

Create a pipeline of Python jobs with stage dependencies, preview via dry run, and confirm to submit the chain.

Instructions

Submit a chain of Python jobs with --dependency=afterok between stages. dryRun preview by default; confirm to submit the chain.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dryRunNo
stagesYes
accountNo
confirmNo
profileNoNamed profile from ~/.risbridge-mcp/config.json. Omit for the default.
projectYesProject name; becomes one directory under the storage workspace.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false, openWorldHint=true), so the bar is lower. The description still adds meaningful behavior beyond them: submission is draft-by-default and requires explicit confirm, and stages are linked by afterok dependency ordering. It omits auth/profile requirements and what happens after confirm.

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?

Two tight sentences, front-loaded with the action and the dry-run safety behavior. No filler or redundancy.

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

Completeness3/5

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

For a mutating, no-output-schema tool with 6 parameters and thin schema coverage, the description covers the dry-run/confirm gate but leaves open what is returned on submit (job IDs?), stage-count limits, and resource defaults. Adequate minimum but with clear gaps.

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

Parameters3/5

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

Schema description coverage is only 33%, so the description must carry weight, and it only clarifies dryRun and confirm semantics (already implied by schema defaults) plus the stage-chaining notion. The nested stage fields (cpus, memGb, gpuCount, walltime, partition, script) get no explanation in either place, so it does not fully compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Submit a chain of Python jobs') plus the defining mechanism (--dependency=afterok between stages), which distinguishes it from single-job siblings like ris_submit_python_job. It doesn't name those siblings explicitly, so it stops short of a 5.

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?

Gives the operational flow ('dryRun preview by default; confirm to submit the chain'), which tells the agent how to sequence dry-run vs. real submission. It says nothing about when to choose a chained pipeline over a single submit tool or ris_plan_run, and no prerequisites are stated.

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