Skip to main content
Glama
Aethis-ai

aethis-mcp

Official
by Aethis-ai

aethis_set_field_spec

Idempotent

Store expected field specs for a project before discovery, so later discoveries auto-validate against them and flag missing fields, wrong types, or invalid enum values.

Instructions

Store the expected field specification for a project. Once set, every aethis_discover_fields call automatically validates discovered fields against this spec. Mismatches (missing fields, wrong types, wrong enum values) generate guidance hints automatically and appear in the validation_result block. Call this BEFORE running aethis_discover_fields when the SME has already defined the field vocabulary. The spec is persisted on the project and survives across sessions. Optionally provide ordered notes for a field. Omit notes to leave existing note guidance unchanged; pass an empty list to clear it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_idYesThe project ID
expected_fieldsYesThe fields the SME expects to be discovered for this project

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.22.0

TDQS

A4.1/5.0
Behavior5/5

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

The description goes well beyond the annotations by disclosing automatic downstream validation ('every aethis_discover_fields call automatically validates discovered fields against this spec'), the resulting mismatch hints in the validation_result block, persistence across sessions, and precise note-handling behavior ('Omit notes to leave existing note guidance unchanged; pass an empty list to clear it'). These are concrete behavioral consequences not captured by readOnlyHint, idempotentHint, or destructiveHint.

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 description is front-loaded with purpose and then adds usage and behavioral detail in a logical order. It is somewhat verbose: the automatic validation and mismatch-hint sentences overlap, and the note-handling sentence duplicates schema text, but no sentence is entirely wasted for a setter with nested configuration.

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?

Given a two-parameter setter with nested expected_fields and no output schema, the description covers purpose, usage timing, downstream effects, persistence, and note semantics. One notable gap remains: it does not specify whether expected_fields replaces the entire existing spec or merges with it, leaving replacement semantics ambiguous.

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%, so the schema already documents both parameters and their nested fields in detail. The description's note-handling sentence largely restates the schema's own notes description ('Omit to leave existing notes unchanged; pass [] to clear them') without adding new semantic detail, so it meets the baseline for high-coverage schemas.

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 states a specific verb and resource: 'Store the expected field specification for a project.' It clearly identifies the action and object, but does not directly differentiate the tool from sibling setters like aethis_validate_fields or aethis_refine_fields within the purpose statement itself; that differentiation comes later as an ordering instruction.

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?

It explicitly says when to call: 'Call this BEFORE running aethis_discover_fields when the SME has already defined the field vocabulary.' That gives a clear context for use, but it does not state when not to use it or name alternative tools for other scenarios, so it falls short of full when/when-not/alternatives guidance.

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