get_forcesList all police forces in England, Wales, and Northern Ireland. Returns force ID and name.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| count | Yes | Total number of police forces | |
| forces | Yes | Array of police forces |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "count": {
+ "description": "Total number of police forces",
+ "type": "number"
+ },
+ "forces": {
+ "description": "Array of police forces",
+ "items": {
+ "properties": {
+ "id": {
+ "description": "Force ID",
+ "type": "string"
+ },
+ "name": {
+ "description": "Force name",
+ "type": "string"
+ }
+ },
+ "required": [
+ "id",
+ "name"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ }
+ },
+ "required": [
+ "count",
+ "forces"
+ ],
+ "type": "object"
+}Input schema / examplesAdded value: +[
+ {}
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description claims to list 'all' police forces, which contradicts the annotation openWorldHint=true, indicating the tool may not return a complete/closed-world set. This is an annotation contradiction, leading to the score of 1.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The entire description is one concise, front-loaded sentence that specifies action, scope, and return fields. Every word earns its place, with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple parameterless list tool with an output schema and comprehensive annotations, the description provides all necessary contextual information (geographic scope, return content). The contradiction with openWorldHint is a transparency issue already scored, but contextually the description is complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the baseline is 4. The description adds no parameter-specific meaning since none exists, and the schema confirms this. No further compensation is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('List all police forces'), scope ('England, Wales, and Northern Ireland'), and return fields ('force ID and name'). This distinguishes it from siblings like get_crimes and get_outcomes, which focus on crime data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage: whenever a list of police forces is needed, likely as reference data for other tools. However, it does not explicitly mention alternatives or exclusionary conditions. Given the tool's simplicity and zero parameters, the context is sufficiently clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several clusters of tools overlap heavily: ask_pipeworx/ask_pipeworx_beta/ask_pipeworx_grounded/deep_research all answer questions, and the five polymarket_* tools require careful reading to distinguish. The three UK police tools are clear, but they sit among many near-duplicate data-query and memory utilities.
Mixed conventions: snake_case verb_noun (get_crimes) coexists with brand-style names (ask_pipeworx), noun phrases (polymarket_arbitrage), and bare verbs (forget, recall). The polymarket_* and ask_pipeworx_* families are internally consistent, but the overall set lacks a single pattern.
34 tools is heavy, and only three relate to the server's stated ukpolice domain, while the rest form a general-purpose data platform. Many meta-tools (suggest_questions, discover_tools, pipeworx_feedback, pipeworx_trending, memory) add bulk relative to the core purpose.
For the actual Pipeworx scope, coverage is strong: query, research, comparisons, subscriptions, memory, and feedback are all present. But for the ukpolice name, it is missing many UK police endpoints (neighborhoods, stop-and-search, etc.) and has no write/update operations, so the surface feels mismatched.