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Check risk before high-risk operations by matching your intent against verified failure lessons. Provides proactive warnings and guards to avoid failed RAG builds, WSL/GPU tasks, or bulk imports.

Instructions

Check risk level before executing high-risk operations. Matches agent intent against lesson triggers to provide proactive warnings. Use before RAG builds, WSL/GPU tasks, bulk imports, or any operation that might fail. Input semantics: intent (required), context (optional). Output schema: JSON with risk level, matched lessons, and guards. Error cases: missing intent. Side effects: none. Auth: none. Rate limits: local stdio process only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intentYesTask intent description (e.g. 'build RAG index from PDFs')
contextNoEnvironment context (e.g. 'WSL, GPU 8GB')

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.17.1

TDQS

A4.7/5.0
Behavior5/5

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

No annotations are provided, so the description carries the full burden. It discloses side effects ('none'), auth ('none'), rate limits ('local stdio process only'), error cases ('missing intent'), and the output format ('JSON with risk level, matched lessons, and guards'). This is comprehensive behavioral disclosure beyond what annotations typically provide.

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 information-dense yet concise, with the primary purpose front-loaded and separate clauses for inputs, output, errors, side effects, auth, and rate limits. Every sentence earns its place, and the structure is logical and scannable.

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?

For a tool with 2 parameters and no output schema, the description is remarkably complete: it covers purpose, usage, parameter roles, expected output, error conditions, side effects, authentication, and rate limits. There is nothing an agent needs to know to call it correctly that is missing.

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 100% with both parameters documented. The description adds minimal value by restating that intent is required and context is optional, but the schema already provides examples. It does not elaborate on semantics beyond the schema, so it stays at the baseline for high coverage.

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 states a specific verb ('Check risk level') and resource ('before executing high-risk operations'), and clearly distinguishes its function (matches intent against lesson triggers) from the sibling tools which are search, retrieval, and submission operations. It leaves no ambiguity about what the tool does.

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?

The description explicitly lists when to use the tool: 'before RAG builds, WSL/GPU tasks, bulk imports, or any operation that might fail.' This provides concrete context and implies it is not needed for safe operations, giving clear guidance without needing to mention alternatives explicitly.

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