Skip to main content
Glama

fitter_validate_config

Validate a Fitter config (JSON or YAML) without executing it. Checks structural rules and returns 'valid' or the validation error.

Instructions

Validate a Fitter config (JSON or YAML) without executing it. Checks the structural rules: item/connector_config/model presence, valid response_type, that the connector has a data source, and compiles every condition/item_condition expression in the model. Returns "valid" or the validation error. Cheap and safe — use it while iterating on a config before calling fitter_run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
configYesFitter CliItem config as a JSON or YAML string to validate without executing it.
Behavior5/5

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

With no annotations, the description fully carries the burden, detailing what it checks (structural rules, condition compilation), that it is cheap and safe, and that it returns 'valid' or error. This comprehensively discloses behavior.

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?

Three sentences, each earning its place: purpose, checks, and usage advice. Front-loaded and succinct with no redundancies.

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?

Given the single parameter and no output schema, the description fully covers purpose, behavior, usage context, and return type. It is complete for effective tool selection.

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 coverage is 100%, so baseline is 3. The description reinforces the config parameter but adds no new parameter-level details beyond the schema description.

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 'Validate a Fitter config (JSON or YAML) without executing it,' clearly specifying the verb and resource. It distinguishes from sibling tools like fitter_run by advising use before calling fitter_run.

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 advises using this tool while iterating on a config before calling fitter_run, providing clear when-to-use context. However, it does not explicitly state when not to use it or mention alternatives for different scenarios.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/PxyUp/fitter'

If you have feedback or need assistance with the MCP directory API, please join our Discord server