Brawler MCP Server (Python)

Policies

policies

Retrieves company policy text for injection into the agent system prompt, so the agent follows organizational rules and constraints during a run.

Instructions

Company policy injected into the agent system prompt.

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": "policies"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 26, 2026

TDQS

B3.1/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. 'Injected into the agent system prompt' is useful behavioral context about how the result is consumed, but it never states that the operation is read-only/non-mutating, whether the policy is scoped or global, or whether the content is static. Risk is low for a zero-parameter tool, so this lands at adequate rather than poor.

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?

A single short sentence, front-loaded and free of filler. It is lean but borders on under-specification rather than being genuinely well-structured as a tool definition.

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?

With an output schema present and no parameters, the description does not need to explain return values, and it correctly stays brief. However, it omits whether the policy content is scoped, current, or authoritative for the session, which are the things an agent needs to decide whether to trust and when to invoke it.

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 and the schema is fully self-describing, so there is no parameter semantics for the description to add. Baseline 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

It identifies the content as company policy and its role (injected into the agent system prompt), which is more than a restated title, but it is a noun phrase with no verb describing what invoking the tool actually does or returns. An agent can guess it fetches policy text, but that is inference rather than a stated purpose.

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?

There is no guidance on when to call this tool, when not to, or how it relates to any of the many siblings (open_ticket, route, style, etc.). The single clause about system-prompt injection implies the tool is context-loading, but no actionable trigger is given.

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

Deploy Server