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Get TSK schema

get_tsk_schema

Returns the TSK domain's generated JSON Schema as raw JSON text to support constraint discovery, structural questions, and validation error resolution.

Instructions

Return the TSK domain's generated JSON Schema (2020-12 dialect) as raw text -- the machine-readable, parsed-JSON view of the document structure, not the markdown view (call get_tsk_template for the authoring starting point). Fetch it for constraint discovery, structural questions, or an unresolved validation error -- never as a mandatory pre-authoring fetch. Generated by specmgr schema and kept current by a pre-commit hook/CI step; includes a $comment schema-layout version marker for detecting a shape change without diffing the whole document.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.37.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the load, and it does: it discloses the raw-text return form, provenance (`specmgr schema` plus pre-commit hook/CI freshness), and a `$comment` layout-version marker for detecting shape changes. It stops short of stating that calls are read-only/no side effects, which is implied but not declared.

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?

Front-loads what is returned and its format, then the alternative, then usage conditions, then provenance — a logical order with no filler. It is a dense, somewhat run-on sentence chain rather than cleanly separated statements, but every clause adds information.

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

Completeness5/5

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

An output schema exists, so return values need not be described; combined with the zero-parameter input, the description covers format, provenance, and usage fully. Nothing an agent needs to call it correctly or interpret the result is missing.

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?

The tool takes zero parameters, so there is little semantics to convey beyond the empty argument object, which the schema already covers at 100% coverage. Baseline 4 applies; the description adds nothing further because nothing further is needed.

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?

States a specific verb (return) and resource (the TSK domain's generated JSON Schema) plus its exact format (raw text, 2020-12 dialect). It explicitly distinguishes itself from the markdown view and from get_tsk_template, so an agent can separate it from the many sibling schema/example/template tools.

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

Usage Guidelines5/5

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

Gives explicit positive triggers (constraint discovery, structural questions, an unresolved validation error) and an explicit negative rule (never a mandatory pre-authoring fetch), then routes the alternative case to get_tsk_template. Both when-to-use and when-not-to-use are covered.

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

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