Skip to main content
Glama
kks32

designsafe-mcp

by kks32

build_workflow_preview

Compile a DAG of job requests to preview the workflow pipeline without running it. Returns deterministic archives and resolved edges for dependency validation.

Instructions

Compile a DAG of job requests without running it.

tasks: [{"task_id", "job", "depends_on": [...], "input_from": {"task_id", "suffix"} (optional)}] Returns the compiled pipeline: deterministic archives, resolved edges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
tasksYes

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 transparency burden and explicitly discloses that the tool compiles and returns a pipeline without running the contained jobs. It adds that output includes 'deterministic archives' and 'resolved edges,' giving useful context about the non-mutating preview behavior, although it does not discuss failure modes or permissions.

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 short and front-loaded with purpose, followed by a compact tasks format and a one-line output summary. The pseudo-code block is somewhat informal but still concise and scannable; no unnecessary prose is present.

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?

Given the workflow-DAG complexity and absence of schema/parameter descriptions, the tool still needs more context to be fully self-sufficient. The output schema covers return details, but the description lacks relationship to sibling validation/submission tools and does not clarify the 'name' parameter or how to construct a complete 'job' object.

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?

The schema provides no descriptions (0% coverage), so the description compensates by specifying the tasks element shape: task_id, job, depends_on, and optional input_from. However, it does not explain the required 'name' parameter or the meaning of 'job' and 'suffix,' leaving part of the parameter semantics implicit.

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 specific action-verb phrase 'Compile a DAG of job requests without running it,' clearly identifying the resource (a DAG of job requests) and the non-execution scope. This distinguishes it from running/submitting siblings and from build_job_request, which targets a single job rather than a workflow DAG.

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 phrase 'without running it' establishes the primary use case: a preview/compilation step before execution. It implies that execution tools like submit_job or job_status are not appropriate for this stage, though it does not explicitly name alternatives or exclusion criteria.

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/kks32/designsafe-mcp'

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