Skip to main content
Glama
kruthin-daacs

Vedha JSON MCP

Get a Vedha canvas

vedha_get_canvas
Read-onlyIdempotent

Retrieve a workflow's semantic model to review its goal, drivers, inputs, guardrails, funnel, entities, and dimensions. Narrow results to a specific dimension and value for targeted analysis.

Instructions

Read one workflow's bounded semantic model (goal, drivers, inputs, guardrails, funnel, entities, dimensions). Optionally narrow to one dimension and value.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
valueNo
canvas_idYes
dimensionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the 'Read' verb aligns with those. The description adds behavioral context beyond annotations by calling the model 'bounded' and by disclosing that results can be narrowed to one dimension and value. No contradiction with annotations is present.

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 exactly two sentences with no wasted words. The primary action and resource are front-loaded, and the optionality is stated in one compact follow-up sentence. The parenthetical enumeration adds useful content without bloat.

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?

For a simple read-only tool, the description covers the core behavior, the bounded scope, and optional filtering. The output schema and annotations handle return format and safety profile. The only notable gap is the unexplained required canvas_id parameter, but the schema enum provides allowed values, so overall completeness is adequate.

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 must compensate by explaining parameters. It mentions 'dimension' and 'value' in the optional narrowing clause, giving those some meaning. However, the required canvas_id parameter is never described or mapped to 'one workflow,' leaving a significant gap for the agent.

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?

The description uses the specific verb 'Read' and identifies the resource as 'one workflow's bounded semantic model' with a concrete list of contents (goal, drivers, inputs, guardrails, funnel, entities, dimensions). This clearly distinguishes it from the sibling audit/diagnosis tools by the nature of the data returned. It doesn't explicitly name a sibling to differentiate, so it misses the top score.

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 when you need a workflow's semantic canvas model, and the optional narrowing clause hints at filtering behavior. However, there is no explicit statement about when to choose this tool over vedha_get_audit or vedha_get_diagnosis, nor any mention of exclusions or prerequisites. Guidance is only implicit.

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