Skip to main content
Glama

platform_eval_sets

Create, read, update, and delete evaluation sets in Arch projects to manage eval assets and CI evidence for workflows.

Instructions

[Arch Evaluate] Arch generates eval assets, runs eval workflows, and reads CI evidence. Manage eval sets through /api/projects/:projectId/evals/sets. Actions: list, get, create, update, delete.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoRequest body for create/update
queryNoOptional query params for list
setIdNoEval set ID for get/update/delete
actionYes
confirmNoSet true for delete
projectIdYesProject ID

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.5.0

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It states only the CRUD actions and endpoint, but says nothing about side effects, permissions, idempotency, or the requirement for 'confirm' on delete (only present in schema). This is insufficient for an agent to anticipate mutation consequences.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief but includes an introductory sentence about Arch that is not directly relevant to this tool's selection, costing it value. The essential CRUD and endpoint info is present, but the extra context dilutes the focus. A tighter description would remove the general Arch statement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a CRUD tool with 6 parameters and no output schema, the description is incomplete. It does not mention response formats, pagination for list, error behaviors, or that delete requires confirm=true. The schema carries most of the burden, but the description fails to connect actions with parameter requirements, leaving gaps for an agent.

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 high (83%), so the baseline is 3. The description adds no additional parameter meaning beyond what the schema already provides. It does not explain how 'body', 'query', or 'setId' interact with specific actions, leaving the agent to rely entirely on the schema.

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 clearly states the resource (eval sets) and the specific operations (list, get, create, update, delete) via the provided endpoint. It distinguishes this tool from siblings like platform_eval_runs and platform_eval_evaluators by focusing on 'sets'. The action enum further clarifies the exact verbs available, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for managing eval sets but does not explicitly compare with alternative tools. It lacks guidance on when to use this over platform_eval_runs or platform_eval_evaluators, and gives no exclusions. The opening sentence about Arch generating eval assets provides broad context but no specific decision framework.

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

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/Koredotcom/agents-mcp-tools'

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