Skip to main content
Glama
Stochastly

Stochastly MCP

by Stochastly

diagnostics_catalog

Read-onlyIdempotent

List every diagnostic code Stochastly can raise, with family, page, and severity, to see what checks can flag or cannot judge in a run. Use diagnostic_explain to detail one code.

Instructions

Requires the Stochastly desktop app: this tool runs inside the app, which is not installed on this machine. Install it from https://stochastly.com/pricing, open it and activate a licence.

List every diagnostic code the app can raise, as diagnostics (code, family, page) and severities.

Use it to know what the checks can hold against a run, and so what they cannot judge yet; explain one code with diagnostic_explain. Needs Stochastly open with an Atelier or Portfolio licence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely useful non-annotation context: the tool only runs inside the desktop app and needs an Atelier or Portfolio licence, which is exactly the kind of prerequisite disclosure the annotations cannot carry.

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 critical prerequisite is front-loaded before any functional text, which is the right ordering for a tool that cannot run without the app. Some redundancy remains: the licence requirement is stated in the opening sentence and repeated at the end ('Needs Stochastly open with an Atelier or Portfolio licence').

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?

With no output schema, the description steps in to describe the return structure; with annotations covering safety, it covers the remaining burden of environment and licence prerequisites. An agent has everything needed to decide whether to call it and whether the call can succeed.

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 the baseline of 4 applies. The description instead documents the output shape (diagnostics grouped as code/family/page plus severities), which is helpful given no output schema exists, but it adds nothing about inputs because there are none.

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 and resource: 'List every diagnostic code the app can raise', and names the returned fields (code, family, page, severities). It is clearly distinguishable from the sibling diagnostic_explain, which it explicitly routes deeper questions to.

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?

Gives a concrete when-to-use rationale ('know what the checks can hold against a run, and so what they cannot judge yet') and names the alternative for the adjacent task ('explain one code with diagnostic_explain'). No explicit when-not conditions, but the routing to the sibling is unambiguous.

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