Framedash Game Telemetry MCP Server

Server Quality Checklist

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Latest release: v0.1.3
Disambiguation3/5
The specialized analytics tools (get_retention, get_funnel, get_insights, etc.) have distinct purposes, but the generic `query` tool can duplicate any of them via SQL, causing potential misselection. Additionally, `get_dashboard` and `get_insights` both surface aggregated metrics, so their boundaries are not perfectly crisp.
Naming Consistency4/5
Most tools follow a consistent `get_<resource>` or `list_<entity>` pattern, making names predictable. However, `query` stands out as a bare verb without a noun, breaking the otherwise uniform convention.
Tool Count5/5
12 tools is within the well-scoped range for a telemetry server. Each tool serves a clear analytics function, and none feel redundant or unnecessary.
Completeness4/5
The tool surface covers the core analytics domain: raw query, dashboards, retention, funnels, insights, heatmaps, projects, maps, content registry, and alert history. Gaps include lack of alert CRUD and project management operations, but for a read-only telemetry MCP server, the coverage is strong.
Average 3.4/5 across 12 of 12 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries full responsibility for behavioral disclosure. It mentions 'aggregated' but does not explain aggregation behavior, default time windows, filtering semantics, or any side effects. It also doesn't clarify whether results are ordered, paginated, or limited beyond what parameters imply.
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?
The description is a single concise sentence that is easy to parse and front-loads the primary function. However, it may be too sparse, omitting important context a longer, still concise description could include.
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?
Given 6 parameters, no output schema, and no annotations, the description is insufficient. It doesn't explain the return structure, typical use cases, or how it differs from the many sibling analytics tools. The lack of behavioral and usage detail makes the tool harder to select or invoke correctly.
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?
The schema has 100% description coverage, with each parameter (metric, group_by, days, limit, etc.) having its own description. The tool description restates the core relationship between metric and group_by but adds no new meaning beyond the schema. Baseline 3 is appropriate because schema handles the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action: 'Get aggregated insights for a metric grouped by a dimension.' It uses a specific verb and identifies the resource/operation. However, it does not explicitly distinguish itself from sibling tools like 'query' or 'get_dashboard', which could also produce aggregated insights.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives such as 'get_retention', 'get_funnel', or 'query'. The description only states what it does, not when it should be chosen or excluded.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 only says 'Analyze event funnels' and mentions the step requirement; it does not disclose defaults (e.g., days=30, window=86400), return format, or mutation effects. This is a significant gap for a tool with no output schema.
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?
The description is brief and front-loaded with the core purpose. It wastes no words, but it is notably terse given the tool has 4 parameters and no other documentation; still, efficiency counts for something.
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?
Considering the tool has 4 parameters, no output schema, and no annotations, the description is far too sparse. It omits default behaviors, expected output, prerequisite setup (e.g., project_id), and any interpretation guidance—leaving the agent under-informed.
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 100%, so the baseline is 3. The description adds no new semantic meaning beyond the schema; the '2-8 event names' note is already present in the schema's description for 'steps'. It does not compensate for parameter behavior or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb + resource ('Analyze event funnels') and adds a key constraint (requires 2-8 event names as steps). This is clear and distinguishes it from siblings like get_retention or get_insights, though it doesn't explicitly call out alternatives.
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?
No guidance on when to use this tool versus alternatives. The only usage hint is the requirement for 2-8 event names, which is more of a parameter constraint than contextual guidance. There are no exclusions or suggested scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description offers no behavioral details beyond the action verb 'Get.' It doesn't disclose output format, default time window behavior, or any side effects, leaving the agent uninformed about what the call returns.
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?
The description is a single concise sentence, earning its place by adding 'player' and 'cohort analysis' beyond the title. It lacks redundancy but could slightly expand to improve clarity.
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 no output schema and no annotations, a simple read tool with two optional parameters is reasonably covered, but the description doesn't explain what 'cohort analysis' returns or how the 'days' parameter affects results, leaving gaps.
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 100% with meaningful descriptions for both 'days' and 'project_id'. The tool description adds nothing beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get player retention cohort analysis' uses a specific verb and resource, clearly indicating it retrieves retention data. It differentiates from siblings like get_funnel or get_insights by naming the retention cohort concept, though it doesn't detail what analysis is performed.
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 provides no guidance on when to use this tool versus sibling analytics tools. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 burden. It implies a read-only operation via 'get' but does not disclose response format, pagination, permissions, or any other behavioral details.
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?
The description is a single sentence, front-loaded with the verb and resource, with zero wasted words. It is highly concise and well-structured.
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 no output schema and no annotations, the description lists metric types but does not clarify the return structure or how this fits with sibling analytics tools. The schema covers parameters, but overall context is merely adequate, not thorough.
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 100% (both days and project_id have descriptions), so the baseline is 3. The description does not add meaning beyond the schema, but the schema already documents the parameters effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get project dashboard metrics' with specific examples (KPIs, daily active users, top events), indicating a distinct resource. However, it does not explicitly differentiate from sibling analytics tools like get_retention or get_funnel.
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?
No guidance is given on when to use this tool versus alternatives. The sibling tools suggest overlapping analytics use cases, and the description provides no exclusions or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the full burden of disclosing behavior. It does reveal return content (event counts, last event time) and implies a read-only operation via the verb 'Get', but it omits any details about side effects, authentication needs, rate limits, or the meaning of 'etc.'. The provided examples give some transparency, but significant behavioral context is missing.
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?
The description is a single sentence that immediately states the action and resource, with parenthetical examples. It is efficient, front-loaded, and contains no filler. The only slight weakness is the vague 'etc.', but this does not undermine the overall conciseness.
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?
This is a simple tool with one parameter and no output schema, but the description leaves gaps: it doesn't clarify how this differs from sibling tools, what 'status' fully includes, or whether project_id is required or optional (though the schema covers the latter). For a basic getter, it is adequate but not fully comprehensive given the lack of annotations and usage guidance.
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?
The only parameter, project_id, is fully described in the input schema as 'Override the default project ID', so schema coverage is 100%. The tool description adds no additional parameter meaning, and since the schema already explains the parameter's purpose, the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a verb ('Get') and resource ('status of a project'), and provides concrete examples of what that status includes ('event counts, last event time'). This distinguishes it from sibling tools like get_dashboard or get_insights, though it does not explicitly name alternatives. The meaning is clear and specific enough for an agent to understand the tool's core function.
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 gives no guidance on when to use this tool versus the many sibling analytics tools (get_dashboard, get_retention, etc.). There is no mention of appropriate contexts, prerequisites, or exclusions. Users are left to infer that it provides a quick project-level overview, but this is not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 burden of disclosing behavioral traits. It does not mention that the operation is read-only, how the default project is determined, or any limitations. The description is purely functional and discloses no safety or side-effect context.
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?
The description is a single, front-loaded sentence: 'List all maps in the project.' It is concise and every word earns its place, with no filler or redundancy.
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?
This is a simple list tool with one optional parameter and schema coverage of 100%, so the description combined with the schema provides adequate context for basic use. However, it does not explain return format, pagination, or how the 'default project' works, which would be helpful for an agent unfamiliar with the domain.
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?
The input schema has 100% coverage for the single parameter project_id, which is described as 'Override the default project ID.' The description adds no parameter information, but the schema adequately explains the parameter. Baseline 3 is appropriate since the schema handles the meaning.
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 uses a specific verb+resource combination: 'List all maps in the project.' This clearly distinguishes it from sibling tools like list_projects, list_content, and list_alerts by focusing on maps. The word 'all' adds scope.
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?
No guidance is given about when to use this tool versus alternatives such as list_projects or list_content. It only states what it does, not when it should be chosen or if there are exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 burden. It does not explicitly state that the operation is read-only, mention any required permissions, or describe the response format. The verb 'List' implies a read operation, but no other behavioral traits are disclosed.
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?
The description is a single, concise sentence that gets straight to the point. There is no fluff or redundancy, and it is front-loaded with the action and object.
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?
Given there is no output schema, the description should at least indicate what is returned (e.g., an array of alert rule objects). It also fails to mention how the default project context works. For a simple list tool this is minimal but still leaves ambiguity 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 coverage is 100%: the only parameter, project_id, has a clear description ('Override the default project ID'). The tool description adds no additional parameter semantics, so the baseline of 3 applies.
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 a specific verb ('List') and resource ('alert rules'), and includes the scope 'in the project'. This distinguishes it from sibling tools like get_alert_history, which would focus on history rather than the rules themselves.
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 usage is implied by the verb and resource—use it when you need alert rules—but there is no explicit mention of when to use it over alternatives or any exclusions. Sibling tools like get_alert_history are not referenced, leaving the differentiation to the description's wording.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 burden of behavioral disclosure. The verb 'List' implies a read-only operation, but the description does not disclose any other behaviors such as pagination, default project scope, authentication requirements, or output format. The mention of 'Override the default project ID' in the schema is not reflected in the description, leaving a behavioral nuance unaddressed.
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?
The description is a single sentence that is concise, front-loaded, and contains no wasted words. It clearly states the action and the object in an efficient manner.
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?
The tool is simple with two optional parameters and no output schema, but the description is minimal. It does not explain that a default project is used unless overridden, nor does it mention what the response contains. Given the lack of annotations and output schema, the description could provide a bit more context about the scope of listing (e.g., default project behavior) to be fully complete.
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?
The input schema provides 100% coverage for both parameters: 'type' as a filter and 'project_id' as an override. The description itself does not add parameter-level meaning beyond the schema, but the schema already describes the parameters adequately. The baseline of 3 applies because the schema does the heavy lifting.
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 tool's purpose: 'List content registry entries' with examples like 'event names, display labels'. This uses a specific verb and resource, and the examples help distinguish it from sibling listing tools like list_projects, list_maps, and list_alerts.
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 listing content registry entries, but it does not explicitly specify when to use this tool versus alternatives. There are no exclusion criteria or references to sibling tools like query or get_dashboard. The usage context is inferred rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. 'Get' and 'trigger/resolve events' imply a safe read operation, but the description does not disclose ordering, default time range, pagination, or any requirements. It provides minimal behavioral context.
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?
The description is a single, front-loaded sentence that conveys the core purpose without any waste. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters and no output schema, the description plus schema covers the essentials. It could mention return format or ordering, but the low complexity makes it adequately complete.
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?
The input schema already provides 100% documentation for both parameters (limit and project_id) with descriptions. The tool description adds no additional parameter meaning, so the baseline of 3 applies.
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 uses a specific verb and resource ('Get alert event history') and clarifies the scope with '(trigger/resolve events)', which distinguishes it from sibling tools like list_alerts. It clearly states what the tool does.
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?
No guidance is provided on when to use this tool versus alternatives, nor any exclusions or context. Sibling tools such as list_alerts and get_dashboard exist, but the description does not explain when this history tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It states the tool returns performance metrics per cell, which adds useful context, but it does not mention any permissions, error conditions, or limitations. For a read-only tool this is somewhat acceptable, though richer detail would improve transparency.
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?
The description is two short sentences, front-loaded with the core purpose and output. Every word earns its place; no unnecessary fluff or repetition of schema details.
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?
The description is adequate for a simple read tool but lacks depth. Since there is no output schema, the description only vaguely mentions 'performance metrics per cell' without detailing the grid structure or response format. It also doesn't mention default behaviors for days/cell_size, though these are in the schema. Overall, it's minimally sufficient but could be more complete.
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 100%, so all parameters are well-documented in the schema. The description adds no additional parameter-level meaning, but the schema already provides defaults, allowed values, and descriptions. Baseline 3 is appropriate.
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 tool gets heatmap grid data for a map and returns performance metrics per cell. This distinguishes it from sibling tools like get_funnel or get_insights by being specific to heatmaps and per-cell metrics.
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 this tool is for heatmap grid data, but it does not explicitly state when to use it over alternatives. There's no mention of exclusions or when another tool might be better, leaving the agent to infer usage from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explicitly discloses that the operation is read-only and details the limit behavior (up to `limit` rows, default 100, max 1000). However, it does not mention error handling, timeouts, or permission requirements, so it is not fully comprehensive.
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?
The description is two sentences, front-loaded with the core action and key constraints. Every phrase earns its place with no redundancy or filler.
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 tool with no output schema, the description explains the input parameters and read-only nature, but it does not describe the return format or any restrictions on SQL syntax beyond read-only. It feels adequate for basic use but leaves some context gaps for a raw SQL endpoint.
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 100%, so the baseline is 3. The description adds some context by naming the ClickHouse events table and explaining the limit default/max, but it does not meaningfully expand on the sql or project_id parameters beyond what the schema already says.
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 states a specific action ('execute a read-only SQL query') and a specific resource ('ClickHouse events table'). It clearly differentiates this generic SQL tool from specialized sibling tools like get_funnel or get_insights, which serve predefined analytics use cases.
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 this is a general-purpose query tool for events data, but it does not explicitly say when to use it instead of the specialized sibling tools. There is no mention of alternatives or when not to use it, leaving the usage guidance implicit rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It indicates a read operation via 'Show', but does not disclose edge-case behavior (e.g., what happens if no project is bound, error handling, or any side effects). Minimal extra context beyond the name.
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?
The description is a single, concise sentence that front-loads the action and resource. Every word adds value, with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description adequately conveys the purpose and scope. It omits details like error responses or exact return format, but given the simplicity, this is a minor gap.
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 has zero parameters and an empty schema, so there is no parameter detail to explain. The description needs to add nothing about parameters, hence the baseline 4.
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 uses a specific verb ('Show') and clearly states the resource ('project') with useful scoping ('bound to the current API key'). This differentiates it from sibling list_* tools that list other resources (maps, content, alerts).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides clear context: use this tool to see the project associated with the current API key. However, it does not explicitly mention when not to use it or mention alternatives, so it stops short of a 5.
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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