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EvalForge Lite

EvalForge Lite

by thejaredchapman
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

set_policy

Define the company policy text that gates prompts before any model is called, ensuring only compliant requests are processed.

Instructions

Set the company policy text used to gate prompts before any model is called.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "policy_text": "<policy_text>"
    },
    "name": "set_policy"
  }
}

Input Schema

NameRequiredDescriptionDefault
policy_textYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that the policy gates prompts before model calls, but omits whether this overwrites an existing policy, what permissions are required, and whether the change is reversible.

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?

A single front-loaded sentence with no filler. It states the action, resource, and effect efficiently.

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

Completeness3/5

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

For a low-complexity one-parameter setter, the description gives the core purpose and parameter role. However, with no annotations or output schema, it leaves mutation semantics, permissions, and usage context underexplained.

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 0%, so the description must compensate. It identifies policy_text as the company policy text used for prompt gating, which adds conceptual meaning beyond the schema, but provides no format, length, or content constraints.

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?

States a specific verb (Set) and resource (company policy text), and adds the runtime effect of gating prompts before model calls. This clearly distinguishes it from the listed siblings, none of which manage policy.

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

Usage Guidelines2/5

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

The description does not say when to use this tool, when not to use it, or how it relates to any alternative. Context implies the use case, but there is no explicit guidance or prerequisite information.

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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