GameAnalytics Documentation
Server Details
Search GameAnalytics docs: Unity, Unreal, iOS, Android SDK and API guides for mobile game analytics.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4/5 across 2 of 2 tools scored.
The two tools have clearly distinct roles: one for searching documentation and one for fetching page content. There is no overlap in purpose.
Both tools follow a consistent 'docs_verb' pattern, with 'fetch' and 'search' clearly indicating their actions. Perfect consistency.
Two tools is on the lower end but can be reasonable for a simple documentation server. However, it may be insufficient if more granular operations are needed.
The server covers search and fetch, which are core for documentation access, but lacks tools like listing categories or filtering. It's minimal but functional.
Available Tools
2 toolsdocs_fetchAInspect
Fetch the complete content of a documentation page. Use this after searching to get the full markdown content of a specific page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | The full URL of the page to fetch (e.g., "https://docs.example.com/docs/getting-started") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral transparency. It states the tool fetches 'complete content' as 'full markdown content,' which is helpful, but does not disclose potential limitations (e.g., rate limits, content size) or side effects. Adequate but not comprehensive.
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?
Two concise sentences, front-loaded with the core purpose, no wasted words. All information is relevant and earns its place.
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 tool with one parameter and no output schema, the description is appropriately complete. It explains the purpose, when to use it, and the parameter meaning. Minor gap: no mention of error handling or possible response format, but acceptable given simplicity.
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?
Schema description coverage is 100%, so the schema already documents the single parameter 'url' well. The description adds value by explaining the context of use and the expected format of the URL, going beyond the schema's brief description.
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 ('Fetch the complete content'), the resource ('documentation page'), and its context of use ('Use this after searching'), effectively distinguishing it from the sibling tool docs_search.
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 explicitly says to use this tool after searching, providing clear context. However, it does not mention when not to use it or any alternatives beyond the implied sibling.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
docs_searchAInspect
Search the documentation for relevant pages. Returns matching documents with URLs, snippets, and relevance scores. Use this to find information across all documentation.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (1-20, default: 16) | |
| query | Yes | The search query string |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries a moderate burden. It accurately describes the tool's read nature and output (URLs, snippets, scores) but does not mention pagination behavior, search algorithm limitations, or the impact of result ordering. It is not contradictory but lacks depth.
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 description is two sentences, concise and front-loaded with the primary action. Every word adds value, no filler.
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?
Given the tool has 2 parameters, no output schema, and a sibling tool docs_fetch, the description is largely complete but could be improved by explicitly mentioning the sibling for correct selection. The return structure (URLs, snippets, scores) is adequately described.
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?
Schema description coverage is 100% for two parameters (query, limit). The description does not add new semantic meaning beyond the schema's already clear parameter descriptions (query string, limit range). Therefore baseline 3 is appropriate.
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 searches documentation for relevant pages and returns matching documents with URLs, snippets, and relevance scores. It explicitly names the scope ('across all documentation'), distinguishing it from a sibling like docs_fetch that likely retrieves a specific page.
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 provides a general use case ('find information across all documentation') but does not explicitly contrast with the sibling tool docs_fetch. It lacks guidance on when to use this versus fetching a specific page, and no exclusion criteria are given.
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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{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
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