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Implicit Core

Implicit Core

by zeitcow
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Python
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implicit_validate_adapter

Read-onlyIdempotent

Validates the built-in warehouse adapter's public plan, source, address, and materialization contract using fixed fixtures without importing user code; custom adapters need SDK tests.

Instructions

Validate the built-in warehouse adapter's public plan/source/address/materialization contract with fixed fixtures. Does not import user code; custom adapters require SDK tests.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "implicit_validate_adapter"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: it operates on fixed fixtures and deliberately does not import user code, which bounds what it can and cannot prove.

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?

Two tight sentences with no filler. The core action and its scope are front-loaded, and the caveat about custom adapters follows immediately after.

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 zero-param, read-only validation tool whose annotations carry the safety profile, the description covers what is validated and its scope limits. The only minor gap is that it does not hint at what a run returns (pass/fail detail), and there is no output schema to fall back on.

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 schema-complete baseline of 4 applies; there is nothing for the description to compensate for, and it adds no misleading parameter claims.

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?

States a specific verb (Validate) and a well-defined resource: the built-in warehouse adapter's public plan/source/address/materialization contract, run against fixed fixtures. It is clearly distinct from siblings like implicit_benchmark or implicit_inspect_state, though it does not explicitly name a sibling to contrast with.

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 clear exclusion and a redirect: 'Does not import user code; custom adapters require SDK tests.' An agent knows this tool only applies to the built-in adapter and where to go for custom adapters, but there is no explicit statement of when to run it versus implicit_benchmark or the inspect tools.

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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