Aedifion MCP Server

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation4/5
Most tools are clearly distinct, targeting specific resources and actions like projects, datapoints, analytics, tasks, and AI. However, some overlap exists, such as multiple 'get_' tools for different aspects of analytics or controls, which could cause confusion if an agent doesn't carefully read descriptions. Overall, the naming and domain separation are strong enough to minimize misselection.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, using snake_case uniformly. Verbs like 'create_', 'delete_', 'get_', 'update_', 'enable_', 'disable_' are applied predictably across resources, making the set easy to navigate and understand. There are no deviations in style or convention.
Tool Count2/5
With 123 tools, the count is excessive for a single server, making it overwhelming and difficult for an agent to manage. While the domain (building management and analytics) is broad, this many tools suggests poor scoping, likely leading to cognitive overload and inefficiency in tool selection, even if the coverage is comprehensive.
Completeness5/5
The tool set provides comprehensive CRUD and lifecycle coverage across all major domains: projects, datapoints, analytics, controls, tasks, AI, users, and more. There are no obvious gaps; for example, each resource has create, read, update, and delete operations, and workflows are fully supported with enabling, disabling, triggering, and status checks.
Average 3/5 across 123 of 123 tools scored. Lowest: 2.3/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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?
No annotations are provided, so the description carries full burden. 'Enable' implies a state-changing mutation, but the description doesn't disclose behavioral traits like what 'enabling' actually does (e.g., starts monitoring, sends notifications), whether it requires specific permissions, if it's reversible via disable_alert, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is inadequate.
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 ('Enable an alert'), followed by a basic parameter note. There's no wasted text, though the under-specification might stem from excessive conciseness rather than efficiency. The two-sentence structure is clear.
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?
Given 1 parameter, no annotations, but an output schema exists, the description is minimally complete but lacks depth. The output schema may cover return values, but the description doesn't address key context like what 'enabling' entails, error conditions, or relations to sibling tools. It's borderline adequate for a simple tool but misses mutation-specific details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It only states 'alert_id: The alert ID', which adds minimal meaning beyond the schema's 'Alert Id' title. It doesn't explain format constraints, where to find alert IDs, or valid ranges. With 1 parameter at 0% coverage, this leaves the parameter poorly documented.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Enable an alert' is a tautology that restates the tool name without adding specificity. It doesn't explain what 'enabling' means operationally (e.g., activating monitoring, resuming notifications) or what resource is affected beyond the generic 'alert'. This provides minimal value beyond the tool name itself.
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 about when to use this tool versus alternatives. The sibling list includes 'disable_alert', 'create_threshold_alert', 'delete_alert', and 'update_threshold_alert', but the description doesn't differentiate this from those related tools or explain prerequisites (e.g., requires an existing alert, might conflict with disabled state).
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 the full burden of behavioral disclosure. While it notes the instance_config is a 'JSON string with fields to update' (indicating partial updates are possible), it lacks critical mutation details: no mention of idempotency, required permissions, error conditions, side effects on existing configurations, or what happens to unspecified fields.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The Args-docstring format is structured and concise, avoiding verbosity. However, the three parameter descriptions waste space stating the obvious ('The instance ID') rather than providing rich examples or constraints, slightly missing the mark for 'every sentence earns its place' in a 0% schema coverage context.
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?
For a mutation tool with zero annotations, no output schema, and undocumented parameters, the description is inadequate. It fails to specify valid fields within instance_config, constraints on updates, or even clarify what constitutes a 'controls instance' despite having many sibling tools in the controls 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?
Schema description coverage is 0%, requiring the description to compensate. It provides minimal semantic value: 'The instance ID' and 'The project's numeric ID' merely restate parameter names, though 'JSON string with fields to update' adds meaningful type/format context for instance_config that the raw schema (type: string) lacks. Sufficient to avoid a lower score but far from comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Update a controls instance' is a direct tautology of the tool name (update_controls_instance). It fails to specify what distinguishes this update operation from sibling tools like create_controls_instance, delete_controls_instance, or enable_controls_instance.
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 provided on when to use this tool versus alternatives (e.g., create_controls_instance for new instances) or prerequisites (e.g., whether the instance must exist first). The description is purely definitional with no contextual usage hints.
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 burden for behavioral disclosure. It only states the action ('Enable') without explaining what enabling entails (e.g., starts processing, activates features), whether it requires specific permissions, if it's reversible via 'disable_analytics_instance', or what side effects might occur. This leaves significant behavioral gaps for a mutation tool.
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 main purpose. The two-sentence structure with a clear Args section is efficient. However, the second sentence ('Args: instance_id: The instance ID.') is tautological and adds no value beyond repeating the parameter name.
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?
For a mutation tool with no annotations, 0% schema coverage, and an output schema (which helps but doesn't compensate), the description is incomplete. It lacks behavioral context, parameter meaning, usage guidance, and doesn't leverage the sibling tool context. The presence of an output schema slightly helps but doesn't address the core gaps in understanding what this tool actually does.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only titles and types. The description adds parameter names but no meaningful semantics - it doesn't explain what an 'instance_id' or 'project_id' represents, how to obtain them, or their relationship. For two required parameters with zero schema documentation, this minimal description is insufficient.
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?
The description states the tool's purpose as 'Enable an analytics instance', which is a clear verb+resource combination. However, it doesn't distinguish this tool from its sibling 'enable_controls_instance' or explain what enabling an analytics instance means in this specific context. The purpose is understandable but lacks differentiation from similar tools.
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 alternatives. It doesn't mention prerequisites (like needing a disabled instance), what happens after enabling, or when to choose this over similar tools like 'enable_controls_instance'. The agent must infer usage from the tool name alone.
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 full burden for behavioral disclosure. It only states the action ('Get results') without mentioning permissions, rate limits, data format, pagination, or error handling. For a tool with 6 parameters and no output schema, this leaves significant behavioral gaps. The description doesn't contradict annotations (none provided).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by a parameter list. However, the parameter explanations are terse and could be more integrated. It avoids redundancy but under-specifies key aspects, leaning toward brevity at the expense of clarity.
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, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain the return format, error conditions, or how parameters interact (e.g., if start/end are null). For a data-fetching tool in a complex analytics context, this leaves the agent with insufficient information to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It lists parameters with brief notes (e.g., 'Start time in ISO 8601 format'), but doesn't explain semantics like what 'units_system' or 'currency_system' entail, valid ranges for IDs, or how null values for optional parameters affect results. This adds minimal value beyond the schema's titles.
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?
The description states the tool 'Get results for an analytics instance', which provides a basic verb+resource combination. However, it's vague about what 'results' specifically means (e.g., metrics, reports, status) and doesn't differentiate from sibling tools like 'get_analytics_instance_status' or 'get_analytics_components_kpi'. The purpose is understandable but lacks specificity.
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. With many sibling analytics tools (e.g., get_analytics_instance, get_analytics_instance_status, get_analytics_components_kpi), the description offers no context about prerequisites, typical use cases, or exclusions. The agent must infer usage from the tool name alone.
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 provided, so description carries full burden. It fails to disclose whether enabling is reversible, if there are side effects, latency, or specific permission requirements. The mutation nature is implied but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Brief and front-loaded, but the Args section repeats information that should ideally live in the schema (though description correctly compensates for empty schema). No wasted sentences, but parameter descriptions are tautological.
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?
For a state-changing operation with no output schema and no annotations, the description is insufficient. It lacks error conditions, success indicators, or state transition details required to safely invoke the tool.
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 has 0% description coverage. The Args section provides minimal mapping ('The instance ID', 'The project's numeric ID'), which adds slight value beyond the schema titles, though 'numeric ID' for project_id is the only substantive addition.
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?
States the specific verb (enable) and resource (controls instance), but merely restates the tool name without explaining what 'enabling' entails (e.g., activation, starting, making available) or how it differs from 'create' or 'update' siblings.
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?
Provides no guidance on when to use this tool versus siblings like create_controls_instance or disable_controls_instance, nor does it mention prerequisites (e.g., instance must exist and be disabled first).
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 provided, so description carries full disclosure burden. It only specifies ISO 8601 format for date parameters. Missing: read-only confirmation, rate limits, data volume expectations, return structure, or error behaviors despite being a data retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Uses compressed 'Args:' format which is information-dense but front-loads the purpose statement appropriately. No wasted prose, though the parameter list format is cramped and could integrate better with the schema.
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?
Lacking annotations, output schema, and with minimal parameter documentation (especially for units_system), the description is insufficient for confident invocation. No indication of what monitoring data fields are returned or time range limits.
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 has 0% description coverage. Description compensates by documenting expected formats (numeric ID, ISO 8601) for 3 of 4 parameters, but 'units_system' is documented only tautologically ('Unit system') without valid values or examples.
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?
States specific verb (Get) and resource (technical monitoring data) with project scope, but fails to differentiate from similar siblings like get_energy_efficiency or get_operational_optimization, making selection ambiguous.
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?
Provides no guidance on when to use this tool versus the many similar data retrieval siblings (get_analytics_kpi_overview, get_project_datapoints, etc.) or prerequisites like required permissions.
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 states 'Delete' which implies a destructive mutation, but fails to disclose critical behavioral traits: whether deletion is permanent, requires specific permissions, has side effects (e.g., cascading deletions), or returns confirmation. For a destructive tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core action, but the Args section is redundant with the schema and adds little value. The structure is acceptable but not optimal—it could integrate parameter context more efficiently.
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?
For a destructive mutation tool with no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks essential context: behavioral details (permanence, side effects), usage prerequisites, and parameter meanings. The agent is left guessing about critical aspects of tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by naming the parameters ('instance_id', 'project_id') but doesn't explain what they represent (e.g., that 'instance_id' identifies the controls instance to delete, or that 'project_id' specifies the containing project). It fails to compensate for the coverage gap.
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 verb ('Delete') and resource ('a controls instance'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'delete_analytics_instance' or 'disable_controls_instance'—the agent must infer that this is a permanent deletion versus a disable operation.
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 like 'disable_controls_instance' or 'delete_analytics_instance'. The description lacks prerequisites, such as whether the instance must be stopped first or if deletion is irreversible.
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 burden for behavioral disclosure. It states this is a 'disable' operation (implying a state change/mutation) but provides no information about permissions required, whether the action is reversible, what happens to associated data, or any rate limits/constraints. This is inadequate for a mutation tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the main purpose, but the parameter documentation is minimal and could be more efficiently integrated. The two-sentence structure is acceptable but not optimally concise given the lack of detail.
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?
For a mutation tool with no annotations, no output schema, and 0% schema description coverage, the description is insufficient. It doesn't explain what 'disable' means operationally, what the expected outcome is, error conditions, or how this differs from deletion/enabling. The context signals indicate this tool needs much more comprehensive documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only titles and types. The description lists the two parameters but adds minimal semantic value—it doesn't explain what an 'instance ID' or 'project ID' represents, their format constraints, or where to find them. This doesn't compensate for the complete lack of schema descriptions.
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 action ('Disable') and the target resource ('a controls instance'), which is specific and unambiguous. However, it doesn't differentiate from its sibling 'disable_analytics_instance' or explain what 'disable' means operationally in this context.
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 like 'delete_controls_instance' or 'enable_controls_instance'. The description lacks context about prerequisites, consequences, or typical use cases for disabling versus other actions.
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, and the description adds no behavioral context beyond the implied read operation. Missing: read-only confirmation, whether results are cached, time-range of aggregation (current day? all-time?), and format of returned KPIs. With zero annotation coverage, this is insufficient disclosure.
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?
Brief and front-loaded with the core purpose. The 'Args:' section uses Python-docstring style which is slightly unconventional for MCP but serves a purpose given the schema's lack of descriptions. No redundant sentences.
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?
Without an output schema or annotations, the description should explain what aggregated results look like (e.g., list of KPIs, averages, sums) and how they differ from 'overview' or component-level queries. For a tool fetching aggregated analytics data, this is dangerously incomplete.
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% (parameter lacks description field). The description compensates by stating project_id is 'The project's numeric ID', which clarifies the semantic meaning. However, it omits where to find this ID or validation constraints, providing only minimal recovery from the schema gap.
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?
States specific action 'Get' and resource 'aggregated KPI results' with scope 'across a project'. However, it fails to distinguish from similar siblings like 'get_analytics_kpi_overview' or 'get_analytics_components_kpi', leaving ambiguity about when to choose this aggregation view versus others.
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 provided on when to use this tool versus alternatives, prerequisites (e.g., whether the analytics instance must be running), or expected latency of aggregate calculations.
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 provided, yet description fails to disclose mutation safety, rate limits, pagination behavior, or data freshness. Only format hint is ISO 8601 for timestamps, leaving significant behavioral gaps.
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?
Compact Args-section format efficiently documents four parameters without verbosity, though the docstring style is slightly inconsistent with typical MCP prose descriptions.
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?
Lacking output schema, annotations, and any explanation of what 'operational optimization data' contains (metrics? recommendations? historical?), the description is insufficient for a 4-parameter data retrieval tool in a complex industrial/IoT 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?
With 0% schema description coverage, the Args section partially compensates by noting project_id is 'numeric' and time fields use 'ISO 8601 format.' However, 'Unit system' is tautological and provides no valid values (metric/imperial) or defaults.
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?
States it retrieves 'operational optimization data for a project' with clear verb (Get) and scope (project), but 'operational optimization' remains vague and doesn't differentiate from siblings like get_energy_efficiency or get_technical_monitoring.
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 versus alternatives (e.g., when to choose this over get_analytics_kpi_overview), nor any mention of prerequisites or constraints beyond the Args list.
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 full burden. It states this is an update operation (implying mutation) but doesn't disclose behavioral traits like required permissions, whether changes are reversible, rate limits, or what the response contains. The description adds minimal context beyond the basic action.
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 main purpose. The Args section is structured but overly terse. While efficient, it sacrifices clarity for brevity, making it somewhat under-specified rather than optimally concise.
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?
Given the tool's complexity (mutation with 3 parameters), lack of annotations, and 0% schema coverage, the description is incomplete. It doesn't explain what an analytics instance is, what fields are updatable, or error handling. However, an output schema exists, so return values needn't be described, slightly mitigating the gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description lists parameters with brief labels but doesn't explain their meaning, formats, or constraints. For example, it doesn't clarify what 'instance_config' should contain (JSON structure, valid fields) or how 'instance_id' and 'project_id' relate. This leaves critical gaps for a 3-parameter tool.
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?
The description states the purpose ('Update an analytics instance') which is clear but vague. It specifies the verb and resource but doesn't explain what an 'analytics instance' is or what fields can be updated. It doesn't distinguish from sibling tools like 'update_controls_instance' or 'update_project' beyond the resource name.
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. There's no mention of prerequisites (e.g., needing an existing instance), error conditions, or relationship to sibling tools like 'create_analytics_instance' or 'delete_analytics_instance'. The agent must infer usage from the tool name alone.
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 burden for behavioral disclosure. While 'Delete' implies a destructive operation, the description doesn't specify whether deletion is permanent, reversible, requires specific permissions, or has side effects. For a destructive tool with zero annotation coverage, this is inadequate transparency.
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 appropriately brief with a clear action statement followed by parameter documentation. The two-sentence structure is efficient, though the Args formatting could be more integrated. There's no unnecessary verbiage, earning a high conciseness score.
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?
For a destructive operation with 2 parameters at 0% schema coverage and no annotations, the description is incomplete. While an output schema exists (which reduces the need to describe return values), the description fails to address critical aspects like deletion consequences, permissions, or error conditions that an agent needs to use this tool safely and effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only types without meaning. The description's Args section names the parameters but adds minimal semantic value - it doesn't explain what a 'datapoint' is, how to obtain IDs, or the relationship between project and datapoint. This doesn't sufficiently compensate for the schema's lack of descriptions.
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 action ('Delete') and resource ('a datapoint'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'delete_project_timeseries' or 'delete_setpoint' that also delete different types of data, so it doesn't reach the highest clarity level.
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 alternatives. There's no mention of prerequisites, when deletion is appropriate, or what happens after deletion. With multiple deletion tools in the sibling list, this lack of differentiation is a significant gap.
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. While 'Delete' implies a destructive mutation, the description doesn't specify whether this action is reversible, requires specific permissions, has side effects, or returns confirmation. For a destructive tool with zero annotation coverage, this is a significant gap in safety and operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with the core action ('Delete a tag'), but the Args section is redundant with the schema and adds no value. While not verbose, the structure includes wasted content that doesn't enhance understanding.
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?
Given that an output schema exists, the description doesn't need to explain return values. However, for a destructive tool with no annotations and 0% schema description coverage, the description is insufficient—it lacks critical behavioral details (e.g., permissions, irreversibility) and parameter semantics, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters are undocumented in the schema. The description only repeats parameter names ('project_id', 'tag_id') without adding any semantic context—no explanation of what these IDs represent, where to find them, or format requirements. This fails to compensate for the schema's lack of descriptions.
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 action ('Delete') and resource ('a tag'), making the purpose immediately understandable. However, it doesn't distinguish this tool from sibling deletion tools like 'delete_project_comment' or 'delete_project_component', which follow the same pattern but target different resources.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., tag must exist), nor does it differentiate from similar tools like 'delete_project' or 'delete_project_timeseries'. The agent must infer usage from the tool name alone.
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 the full burden of behavioral disclosure. It implies a mutation ('Disable'), but lacks details on permissions required, whether the action is reversible, rate limits, or what happens to the instance after disabling. This leaves significant gaps for an agent to understand the tool's behavior.
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 front-loaded with the core action ('Disable an analytics instance') and uses a simple two-line Args section. It avoids unnecessary words, though the Args formatting could be more integrated. Overall, it's efficient with little waste.
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?
For a mutation tool with no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks behavioral context, parameter details, and output information, making it inadequate for an agent to use the tool effectively without additional assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal semantics by naming the parameters ('instance_id' and 'project_id') but doesn't explain their formats, sources, or relationships. This is insufficient to compensate for the lack of schema documentation.
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 verb ('Disable') and resource ('an analytics instance'), making the purpose specific and understandable. It distinguishes from siblings like 'enable_analytics_instance' and 'delete_analytics_instance' by focusing on disabling rather than enabling or deleting, though it doesn't explicitly contrast them in the text.
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 like 'enable_analytics_instance' or 'delete_analytics_instance', nor does it mention prerequisites such as needing an existing instance. The description only states what it does without context for usage.
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. It states the tool is for getting status, implying a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, error conditions, or what the status output entails (e.g., running, stopped, error). For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 appropriately sized and front-loaded, with the main purpose stated clearly in the first sentence. The parameter list is concise and directly relevant. There's no unnecessary verbosity, making it easy to scan, though the structure could be slightly improved by integrating parameter details more seamlessly.
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 the complexity (a status-checking tool with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the status output includes, potential error scenarios, or dependencies on other tools (e.g., needing a created instance first). For a tool in this context, more detail is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, meaning parameters are undocumented in the schema. The description lists the parameters ('instance_id' and 'project_id') and briefly describes them, adding some semantic value (e.g., 'instance_id: The instance ID.'). However, it doesn't fully compensate for the coverage gap—it lacks details like format constraints, examples, or how these IDs relate to other tools, leaving parameters partially unclear.
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 purpose: 'Get the status of an analytics instance.' It specifies the verb ('Get') and resource ('analytics instance'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_analytics_instance' or 'get_analytics_status', which might have overlapping or related purposes.
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 alternatives. It doesn't mention prerequisites, such as needing an existing analytics instance, or compare it to siblings like 'get_analytics_instance' (which might retrieve details) or 'get_analytics_status' (which could be broader). Without such context, an AI agent might struggle to select the right tool.
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 provided, so description carries full burden, yet it only states 'Get' implying read-only safety without describing what data is returned, error conditions, or whether this triggers any background processing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Brief and front-loaded, but the Args docstring format is unusual for MCP and the brevity squanders opportunity to address behavioral gaps given zero annotation coverage.
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?
Simple single-parameter tool, but lacks output schema description, rate limit warnings, or domain context needed to navigate the dense sibling analytics toolset (instances, KPIs, components).
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?
With 0% schema description coverage, the Args section successfully adds critical semantics: 'project_id' is 'The project's numeric ID', clarifying ownership and format beyond the schema's bare 'Project Id' title.
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?
States specific verb 'Get' and resource 'analytics status overview', but 'overview' is vague and fails to distinguish from sibling 'get_analytics_instance_status', which appears to be instance-level versus this project-level 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?
Provides no guidance on when to use this versus alternatives like 'get_analytics_instance_status' or 'get_project'. No mention of prerequisites or when not to use.
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. It states this is a 'Get' operation, implying it's read-only, but doesn't confirm if it's safe, whether it requires authentication, what happens on errors, or if there are rate limits. The description adds minimal behavioral context beyond the basic action.
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 concise and well-structured: a clear purpose statement followed by a bullet-point-style 'Args' section. Every sentence serves a purpose, with no redundant information. However, the 'Args' formatting could be slightly more integrated, but it remains efficient.
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 the tool's complexity (a read operation with 2 required parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'details' are returned, potential errors, authentication needs, or how this tool differs from siblings. For a tool in a rich sibling set, this leaves the agent with insufficient context to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that lists the two parameters ('instance_id' and 'project_id') but only adds minimal semantics ('The instance ID' and 'The project's numeric ID'). This doesn't explain what these IDs represent, where to find them, or their format constraints, leaving significant gaps in understanding.
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 purpose: 'Get a controls instance's details.' It uses a specific verb ('Get') and identifies the resource ('controls instance's details'). However, it doesn't differentiate from sibling tools like 'get_controls_instances' (plural) or 'get_controls_instance_status', which might retrieve different information about controls instances.
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 alternatives. It doesn't mention sibling tools like 'get_controls_instances' (for listing instances) or 'get_controls_instance_status' (for status information), nor does it specify prerequisites or exclusions for usage.
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. It does not explain what 'status' means (e.g., running, stopped, error states), what the response format looks like, or whether errors are thrown for invalid IDs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence is appropriately concise. However, the 'Args:' block uses Python docstring formatting which is suboptimal for MCP tool descriptions; parameter semantics should be integrated into natural language or rely on well-documented schemas.
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 simple 2-parameter read operation without an output schema, the description is minimally sufficient to invoke the tool, though it lacks important context about the controls domain (what status values to expect, relationship to instance lifecycle).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring the description to compensate. The Args section offers tautological descriptions ('The instance ID' for instance_id) with only marginal value (noting project_id is 'numeric'). It fails to explain acceptable ID formats or how to obtain valid instance IDs.
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?
States a specific verb (Get) and resource (status of a controls instance) clearly matching the tool name. However, it fails to differentiate from sibling tool 'get_controls_instance' which likely retrieves full instance metadata versus just status.
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?
Provides no guidance on when to use this tool versus 'get_controls_instance' or other related siblings. No mention of prerequisites, error conditions, or typical usage patterns.
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 full burden. It states 'Get a specific logbook' which implies a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or what happens if the logbook doesn't exist. For a retrieval tool with zero annotation coverage, this leaves significant gaps.
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 appropriately sized and front-loaded with the core purpose ('Get a specific logbook'). The parameter explanations are brief and directly relevant. There's minimal waste, though the structure could be slightly improved by integrating parameter details more seamlessly rather than as a separate 'Args:' section.
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?
Given that there's an output schema (which handles return values), no annotations, and simple parameters with 0% schema coverage, the description is moderately complete. It covers the basic purpose and parameter meanings, but lacks behavioral context (e.g., error handling, permissions) that would be helpful for a tool with no annotations.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantics by explaining 'project_id: The project's numeric ID' and 'logbook_id: The logbook ID', which clarifies what these IDs refer to. However, it doesn't provide format details, constraints, or examples, leaving room for improvement.
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?
The description states the tool 'Get a specific logbook', which clearly indicates a retrieval operation on a logbook resource. However, it doesn't distinguish this from sibling tools like 'get_logbooks' (plural) or 'create_logbook', leaving ambiguity about when to use this versus the list operation.
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. With sibling tools including 'get_logbooks' (likely for listing) and 'create_logbook', the description doesn't indicate that this is for retrieving a single, specific logbook by ID rather than listing all logbooks or creating new ones.
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 full burden. It states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what format the status information returns. The description provides minimal behavioral context beyond the basic operation type.
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 structured with a clear purpose statement followed by parameter explanations. There's no unnecessary information, and the two-sentence format is efficient. However, the parameter explanations could be more informative while maintaining 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?
Given that there's an output schema (which handles return values), no annotations, and only 2 parameters with 0% schema coverage, the description provides basic purpose and parameter names. It's minimally adequate but lacks context about what 'status' entails, usage scenarios, or behavioral details. For a simple read operation, it meets minimum viability but has clear 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 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that names both parameters (project_id, setpoint_id) and provides brief explanations ('The project's numeric ID', 'The setpoint ID'), adding some semantic value. However, it doesn't explain what these IDs represent, where to find them, or provide format examples. This partially compensates for the schema gap but not fully.
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?
The description states 'Get the status of a setpoint' which is a clear verb+resource combination, but it's quite generic. It doesn't specify what 'status' means in this context or differentiate from sibling tools like 'get_project_setpoints' or 'write_setpoint'. The purpose is understandable but lacks specificity.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or distinguish it from related tools like 'get_project_setpoints' (which might list setpoints) or 'write_setpoint' (which modifies setpoints). The agent receives no usage direction.
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 burden but offers minimal behavioral insight. It implies a write operation ('Map') but doesn't disclose permissions needed, side effects, idempotency, or what happens if the mapping already exists. This is inadequate for a mutation tool with zero annotation coverage.
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, followed by a parameter list. However, the parameter section is redundant with the schema and adds no value, slightly reducing efficiency. Overall, it's concise but could be more structured.
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?
For a 4-parameter mutation tool with no annotations, 0% schema coverage, and an output schema (which helps but isn't described), the description is insufficient. It lacks behavioral details, parameter explanations, and usage context, making it incomplete for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description lists parameter names but adds no semantic meaning—it doesn't explain what 'cip_id' or 'datapoint_id' represent, their formats, or relationships. This fails to compensate for the schema gap.
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 action ('Map') and the resources involved ('component pin' to 'datapoint'), making the purpose understandable. However, it doesn't explicitly differentiate from its sibling 'unmap_component_pin' or explain what 'mapping' entails in this context, preventing a perfect score.
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 alternatives, prerequisites, or constraints. It doesn't mention the sibling 'unmap_component_pin' for reversing mappings or other related tools like 'get_component_pins', leaving the agent with no usage context.
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 the full burden of behavioral disclosure. It states the operation but fails to disclose mutation characteristics, side effects, permissions required, or what happens if the user isn't currently assigned (error vs silent success).
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?
Appropriately brief with no filler sentences. The Args block is structured clearly, and given the 0% schema coverage, its inclusion is necessary rather than wasteful.
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?
Although the tool has only two simple parameters and an output schema exists, the description misses critical safety context for a mutation operation. Without annotations or behavioral notes, the agent cannot assess the impact of calling this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, requiring heavy description compensation. The Args block provides only 'The task ID' (redundant with title) and 'The user ID to unassign' (minimal semantic addition). It lacks format constraints, ID sources, or whether these are internal vs external IDs.
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?
Provides a specific verb ('Unassign') and resource ('task') with clear scope ('from a user'). However, it does not explicitly differentiate from sibling tool 'assign_task' or clarify when to use unassignment versus reassignment.
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?
Contains no guidance on when to use this tool versus alternatives, prerequisites (e.g., task must currently be assigned to the user), or failure modes. The agent has no signal for whether this is safe to call idempotently.
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 burden for behavioral disclosure. It states this is an 'Add' operation (implying creation/mutation) but provides no information about side effects, permissions required, whether comments are editable/deletable, rate limits, or what happens on success/failure. The existence of 'delete_project_comment' as a sibling suggests comments can be removed, but this isn't mentioned in the description.
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 appropriately brief and front-loaded with the core purpose. The two-sentence structure is efficient, though the parameter documentation uses basic formatting rather than integrated prose. There's no wasted text, but the parameter section feels somewhat disconnected from the main description.
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?
Given that this is a mutation tool with no annotations, 0% schema description coverage, but with an output schema present, the description provides the minimum viable information. It states what the tool does and documents the two parameters at a basic level. However, for a write operation that likely requires specific permissions and has behavioral implications, more context about success conditions, error cases, and relationship to other comment operations would be valuable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides only basic type information. The description adds minimal parameter context: it clarifies that 'project_id' is 'numeric' (though the schema already shows integer type) and that 'text' contains 'Comment text.' This doesn't provide format requirements, length limits, or examples. For a mutation tool with zero schema description coverage, this is insufficient compensation.
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 action ('Add a comment') and target resource ('to a project'), making the purpose immediately understandable. It distinguishes from sibling tools like 'add_task_comment' by specifying the project context, though it doesn't explicitly contrast with 'add_project_component' or 'add_project_tag' which operate on the same resource type.
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 about when to use this tool versus alternatives. While the description implies it's for adding comments to projects, it doesn't mention when to choose this over 'add_task_comment' (for tasks) or how it relates to 'get_project_comments' (for reading comments). There's no information about prerequisites, permissions needed, or typical use cases.
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 the full burden of behavioral disclosure. It states the tool deletes a plot view, implying a destructive mutation, but doesn't specify whether deletion is permanent, requires permissions, or has side effects. This is inadequate for a mutation tool with zero annotation coverage.
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. The Args section is organized but could be more integrated. There's no wasted text, though it risks under-specification.
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 deletion tool with 2 parameters, 0% schema coverage, and no annotations, the description is minimal. The presence of an output schema mitigates the need to describe return values, but key behavioral and parametric details are missing, making it only partially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description lists the parameters but only repeats their names without explaining what they represent (e.g., what a plot view ID is, how to obtain it). It adds minimal value beyond the schema's structure.
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 action ('Delete') and the resource ('a plot view'), making the purpose immediately understandable. It distinguishes from siblings like 'delete_project' or 'delete_logbook' by specifying the exact resource type, though it doesn't explicitly contrast with similar deletion tools.
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. The description doesn't mention prerequisites, consequences, or relationships to sibling tools like 'create_plot_view' or 'get_plot_views', leaving the agent to infer usage context.
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, and the description omits critical behavioral details: it does not specify the aggregation method, time range, read-only nature, pagination behavior, or what constitutes a 'component' in this context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief, but the 'Args' section is redundant with the JSON schema and wastes space restating the single parameter name. The information could be integrated more efficiently without the pseudo-docstring format.
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?
For an analytics tool with complex output (implied by 'KPI results'), the description is inadequate. It lacks output format details, component definition, KPI enumeration, and time-range specifications that would be necessary for effective agent use.
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?
With 0% schema description coverage, the description carries the full burden of parameter documentation. The 'Args' section adds minimal semantic value by specifying 'numeric ID' for project_id, but lacks details on how to obtain the ID, valid ranges, or constraints.
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 identifies the action (Get), resource (aggregated KPI results), and scope (per component). However, it fails to differentiate from sibling tools like get_analytics_kpi_aggregation and get_analytics_kpi_overview, leaving ambiguity about when to prefer this endpoint.
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 provided on when to use this tool versus the similar KPI-related siblings (get_analytics_kpi_aggregation, get_analytics_kpi_overview) or what prerequisites (like an existing analytics instance) might be required.
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 the full burden of behavioral disclosure. It states this is an update operation, implying mutation, but doesn't cover critical aspects like required permissions, whether changes are reversible, rate limits, or error handling. This leaves significant gaps for a tool that modifies configurations.
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, followed by a simple parameter list. It avoids unnecessary fluff, though the parameter section could be more informative. Overall, it's efficient but not perfectly 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?
Given that an output schema exists, the description doesn't need to explain return values. However, with no annotations, 0% schema coverage, and a mutation tool, the description is incomplete—it lacks behavioral context and detailed parameter semantics, making it only minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the schema provides no parameter details. The description adds minimal value: it names the parameters ('alert_id' and 'alert_details') and vaguely describes 'alert_details' as a 'JSON string with fields to update', but doesn't explain the JSON structure, valid fields, or examples. This is insufficient for two undocumented parameters.
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 verb 'update' and the resource 'threshold alert's configuration', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'update_analytics_instance' or 'update_controls_instance' beyond the resource name, which is why it doesn't reach a perfect score.
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. The description lacks context about prerequisites (e.g., needing an existing alert), exclusions, or comparisons to other update tools in the sibling list, leaving the agent without usage direction.
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 states the tool can 'overwrite' a tag, indicating mutation behavior, but doesn't disclose other critical traits: whether it requires specific permissions, if changes are reversible, rate limits, or what happens on success/failure. The description is minimal and lacks behavioral context beyond the basic action.
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 front-loaded with the core purpose in the first sentence, followed by a structured Args section. It's efficient with minimal waste, though the Args formatting could be more integrated. Every sentence serves a purpose, but the structure is slightly fragmented between description and parameter list.
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?
Given the tool has 4 parameters with 0% schema coverage and an output schema (which reduces need to describe return values), the description is moderately complete. It covers the basic action and parameters but lacks behavioral details, usage context, and deeper parameter semantics. For a mutation tool with no annotations, it should do more to compensate for the missing structured data.
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 0%, so the schema provides no parameter descriptions. The description lists all four parameters with brief labels (e.g., 'Tag key', 'Tag value'), adding some semantic meaning beyond the schema's titles. However, it doesn't explain parameter relationships (e.g., how tag_id, key, and value interact) or provide examples, leaving gaps in understanding.
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 action ('Add or overwrite') and target resource ('a tag on a datapoint'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_project_tag' or 'get_project_tags', though the verb 'add/overwrite' implies creation/modification versus deletion or retrieval.
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 alternatives. It doesn't mention prerequisites (e.g., needing an existing project or tag), exclusions, or comparisons to sibling tools like 'update_project' or 'delete_project_tag'. Usage context is implied but 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 full burden. 'Add a comment' implies a write/mutation operation, but the description doesn't disclose behavioral traits like required permissions, whether comments are editable/deletable, rate limits, or what happens on success/failure. This leaves significant gaps for a mutation tool.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The 'Args:' section is structured but could be more integrated. There's minimal waste, though it could be slightly more polished (e.g., merging the Args into a single cohesive paragraph).
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?
Given a mutation tool with no annotations, 0% schema coverage, but an output schema exists, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context, usage guidelines, and error handling. The output schema may help with return values, but overall completeness is limited for safe tool invocation.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantics ('task_id: The task ID', 'text: Comment text'), which clarifies what each parameter represents. However, it doesn't provide format details (e.g., task ID format, text constraints), leaving some ambiguity. This partial compensation warrants a baseline score.
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 action ('Add a comment') and target resource ('to a task'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'add_project_comment' or 'delete_task_comment', which would require specifying this is specifically for task comments versus project comments or deletion operations.
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 alternatives like 'add_project_comment' or 'delete_task_comment'. It also doesn't mention prerequisites (e.g., needing a valid task ID) or constraints (e.g., comment length limits). The agent must infer usage from context alone.
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. It states the tool 'Get[s] all messages,' implying a read-only operation, but doesn't clarify permissions, rate limits, pagination, or error handling. For a tool with no annotation coverage, this is insufficient to ensure safe and effective use.
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 concise and front-loaded, with the main purpose stated first. The additional 'Args' section is brief and relevant. However, the second sentence could be integrated more smoothly, and there's slight redundancy in stating the parameter name twice, but overall it's efficient with minimal waste.
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?
Given the tool has an output schema (which handles return values) and only one parameter, the description is somewhat complete. However, with no annotations and low schema coverage, it lacks behavioral context and detailed parameter guidance. It's adequate for a simple read operation but misses opportunities to clarify usage and constraints.
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 description coverage is 0%, meaning the input schema lacks descriptions for parameters. The description adds a brief note: 'thread_id: The thread identifier,' which provides basic semantics but lacks details like format, source, or constraints. Since there's only one parameter, the baseline is 4, but the minimal explanation reduces it to 3, as it doesn't fully compensate for the schema gap.
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 purpose: 'Get all messages in an AI conversation thread.' It specifies the verb ('Get') and resource ('messages in an AI conversation thread'), making it easy to understand. However, it doesn't explicitly differentiate from its sibling 'ai_get_threads' (which likely lists threads rather than messages within a thread), so it misses the highest score.
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 alternatives. It doesn't mention prerequisites (e.g., needing an existing thread_id), exclusions, or comparisons with related tools like 'ai_get_threads' or 'ai_chat'. This leaves the agent without context for tool selection.
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 the full burden of behavioral disclosure. It states this is a list operation, implying read-only behavior, but doesn't mention authentication requirements, rate limits, error conditions, or what the output contains. The pagination parameters are mentioned but without explaining default behavior or constraints.
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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient, though the parameter explanations could be integrated more smoothly rather than as a separate 'Args:' section.
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 read-only list tool with 2 optional parameters and an output schema (which handles return values), the description provides adequate basic information. However, with no annotations and 0% schema description coverage, it should ideally explain more about authentication context, pagination defaults, and what 'AI conversation threads' specifically means in this system.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantic meaning by identifying 'page' and 'per_page' as pagination parameters, which is helpful. However, it doesn't explain acceptable ranges, default values, or what happens when parameters are null (as allowed by the schema).
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 purpose with a specific verb ('List') and resource ('all AI conversation threads for the current user'). It distinguishes from sibling 'ai_get_thread' (singular) by indicating it retrieves multiple threads. However, it doesn't explicitly differentiate from other list-style tools like 'get_logbooks' or 'get_analytics_instances' beyond the resource type.
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. While it's clear this lists AI threads, there's no mention of prerequisites, when to use pagination parameters, or how it relates to other thread management tools like 'ai_delete_thread' or 'ai_chat'.
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 burden for behavioral disclosure. It states the tool performs an assignment operation (implying mutation) but doesn't describe what happens during assignment: whether it overwrites existing assignments, requires specific permissions, triggers notifications, or has side effects. For a mutation tool with zero annotation coverage, this is insufficient.
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 appropriately brief with two sentences: a purpose statement and parameter listing. The structure is front-loaded with the core action. However, the parameter section could be integrated more smoothly rather than as a separate 'Args' block.
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?
Given that an output schema exists, the description doesn't need to explain return values. However, for a mutation tool with no annotations, 0% schema description coverage, and two parameters, the description should provide more context about behavioral outcomes, error conditions, and relationships to sibling tools like 'unassign_task'.
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 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that names both parameters (task_id, user_id) and specifies they are IDs, adding basic semantics. However, it doesn't explain format expectations, valid ranges, or where to obtain these IDs, leaving significant gaps.
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 action ('Assign a task') and the target ('to a user'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'unassign_task' or explain how assignment differs from other task-related operations like 'update_task' or 'create_task'.
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 alternatives. It doesn't mention prerequisites (e.g., task must exist, user must have appropriate permissions), when assignment might fail, or when to use 'unassign_task' instead. The agent must infer usage from context alone.
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 present, so the description carries the full burden of behavioral disclosure. While 'Create' implies mutation, the description omits critical details: whether creation is idempotent, if the instance is enabled automatically (vs requiring 'enable_controls_instance'), required permissions, or error conditions.
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 compact and front-loaded with the core purpose. The 'Args' format, while slightly verbose, clearly maps parameters to their semantics without redundant prose. No sentences waste space on tautology or generic filler.
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?
For a creation tool with zero schema annotations and no output schema, the description is insufficient. It lacks explanation of what constitutes a 'controls instance', what the operation returns (e.g., the created instance ID), or side effects on the system state.
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?
With 0% schema description coverage, the description compensates by providing critical type information: 'project_id' is specified as a 'numeric ID' (clarifying the integer type) and 'instance_config' is identified as a 'JSON string' (crucial since the schema only lists 'string'). However, it fails to describe the expected structure or required fields within the JSON configuration.
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?
States a specific verb ('Create') and resource ('controls instance'), providing clear identification. However, it fails to distinguish from the similar sibling 'create_analytics_instance' or clarify what distinguishes a 'controls' instance from other instance types.
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?
Provides no guidance on when to use this versus 'update_controls_instance', prerequisites for creation (e.g., existing project), or when to prefer this over 'create_analytics_instance'. The 'Args' format documents parameters but does not explain usage context.
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 burden for behavioral disclosure. While 'Create' implies a write/mutation operation, the description doesn't address permissions required, whether entries are editable/deletable, rate limits, or what happens on success/failure. The existence of 'delete_logbook_entry' as a sibling suggests entries can be removed, but this isn't mentioned in the description.
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 efficiently structured with a clear purpose statement followed by parameter documentation. The two-sentence format with bullet-point Args is well-organized and front-loaded. However, the Args section could be more integrated with the description rather than appearing as a separate documentation block.
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?
Given that an output schema exists (which should document return values), the description doesn't need to explain return values. However, for a 4-parameter mutation tool with no annotations and 0% schema description coverage, the description should provide more context about constraints, permissions, and error conditions. The basic parameter documentation is insufficient for full understanding.
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 Args section lists all 4 parameters with brief labels, but with 0% schema description coverage, this provides only basic semantic context. The description doesn't explain what constitutes valid project_id/logbook_id values, title/body_text constraints, or relationships between these parameters. It compensates minimally for the schema coverage gap.
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 action ('Create a new entry') and resource ('in a logbook'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_logbook' or 'delete_logbook_entry', which would require more specific context about what distinguishes this particular creation operation.
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 alternatives. There are many sibling creation tools (create_logbook, create_project, create_task, etc.), but no indication of what contexts or prerequisites make this tool appropriate. The Args section documents parameters but doesn't provide usage context.
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. It states this is a creation operation, implying mutation, but doesn't cover permissions needed, whether it's idempotent, rate limits, or what happens on success/failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.
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 main purpose. The two-sentence structure with an 'Args:' section is efficient, though the parameter explanations are minimal. There's no wasted text, but it could be more informative without losing 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?
Given that there's an output schema (which handles return values), no annotations, and low schema coverage, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral details, usage context, and deeper parameter semantics. For a mutation tool, this leaves gaps in completeness.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it clarifies that 'project_id' is numeric and 'plot_config' is a JSON string, but doesn't explain what a 'plot configuration' entails, valid formats, or examples. This partially compensates but leaves key details unclear.
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 action ('Create a new plot view') and identifies the resource ('plot view'), which is specific and unambiguous. However, it doesn't differentiate this tool from sibling tools like 'create_analytics_instance' or 'create_controls_instance' that also create resources, nor does it explain what a 'plot view' is in this context.
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. The description doesn't mention prerequisites (e.g., needing an existing project), exclusions, or related tools like 'get_plot_views' or 'delete_plot_view' from the sibling list. It's a basic statement of function without context.
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 provided, so description carries full burden. Fails to disclose side effects, uniqueness constraints on project names, what the output schema returns, or permission requirements. Only states the basic creation action.
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?
Brief and front-loaded. The 'Args:' format is slightly unconventional for MCP but efficiently documents the two parameters without excessive verbosity. No wasted sentences.
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?
Despite having an output schema, the description does not indicate what data is returned (e.g., project ID, full object). For a creation tool with 0% schema coverage and no annotations, lacks critical context about success behavior, error conditions, and constraints.
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 0%, so description compensates by providing 'Project name' and 'Project description' labels. However, it omits that description defaults to null (optional) and provides no format constraints or validation rules for name.
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?
States 'Create a new project in the company' with clear verb and resource. However, it does not explicitly distinguish from sibling creation tools like create_task or create_logbook, though 'project' specificity provides implicit differentiation.
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, nor any prerequisites (e.g., permissions, company existence). Does not mention that name is required while description is optional.
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. It states 'Delete an alert', implying a destructive mutation, but fails to describe critical traits: whether deletion is permanent, requires specific permissions, has side effects (e.g., on related data), or returns confirmation. This is inadequate for a mutation tool with zero annotation coverage.
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 ('Delete an alert.'), followed by parameter details. It avoids unnecessary words, but the 'Args' section could be integrated more smoothly. Overall, it's efficient with minimal waste.
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 this is a destructive mutation tool with no annotations, 0% schema description coverage, and an output schema (which might help), the description is insufficient. It lacks behavioral details, usage context, and parameter semantics beyond a basic label, failing to compensate for the missing structured information.
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 description includes an 'Args' section that documents the single parameter 'alert_id', adding meaning beyond the input schema, which has 0% description coverage. However, it only states 'The alert ID' without explaining format, source, or validation rules. With one parameter and low schema coverage, this provides basic but incomplete semantic context.
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 verb 'Delete' and the resource 'an alert', making the purpose unambiguous. It distinguishes this as a deletion operation, which is different from sibling tools like 'disable_alert' or 'create_threshold_alert'. However, it doesn't specify what type of alert (e.g., threshold alert) or from what context (e.g., project), which prevents a perfect score.
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 alternatives like 'disable_alert' or other deletion tools (e.g., 'delete_project', 'delete_task'). It lacks context about prerequisites, such as whether the alert must be disabled first or if deletion is irreversible, leaving the agent without usage instructions.
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 burden for behavioral disclosure. It states the action is 'Delete,' implying a destructive, irreversible operation, but doesn't elaborate on permissions required, side effects (e.g., data loss), confirmation steps, or error conditions. For a destructive tool with zero annotation coverage, this is a significant gap in safety and operational context.
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 front-loaded with the core purpose in the first sentence, followed by parameter explanations. It avoids unnecessary words, though the parameter section could be integrated more seamlessly. Overall, it's efficient with minimal waste, earning a high score for 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?
Given the tool's destructive nature, no annotations, and an output schema (which reduces need to describe returns), the description is moderately complete. It covers the basic action and parameters but lacks critical behavioral details like permissions, irreversibility, or error handling. For a deletion tool, this is adequate but leaves safety and operational gaps that could hinder correct usage.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantics by naming the parameters ('instance_id' and 'project_id') and briefly explaining them, but doesn't clarify format expectations (e.g., where to find these IDs), constraints, or relationships between parameters. This provides marginal value over the bare schema, compensating partially but not fully for the coverage gap.
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 action ('Delete') and resource ('analytics instance'), making the purpose unambiguous. It distinguishes from siblings like 'disable_analytics_instance' by specifying permanent removal rather than temporary deactivation. However, it doesn't explicitly contrast with other deletion tools (e.g., 'delete_controls_instance'), leaving some sibling differentiation incomplete.
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 like 'disable_analytics_instance' or other deletion tools. The description lacks context about prerequisites (e.g., whether the instance must be stopped first), consequences, or typical scenarios for deletion versus disabling. This leaves the agent without clear decision-making criteria.
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. While 'Delete' implies a destructive mutation, it doesn't specify whether deletion is permanent, reversible, or cascades to associated data. It also omits critical details like authentication requirements, rate limits, or error conditions, leaving significant gaps for a destructive operation.
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 in the first sentence, followed by a structured 'Args' section. There's no unnecessary verbiage, though the formatting with a blank line could be slightly improved for compactness.
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?
Given the tool's destructive nature, lack of annotations, and 0% schema coverage, the description is minimally adequate but incomplete. It covers the basic purpose and parameter, but omits behavioral details crucial for safe invocation. The presence of an output schema (not provided in details) might mitigate some gaps, but the description itself doesn't reference return values or error handling.
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 description coverage is 0%, but the description includes an 'Args' section that documents the single parameter 'user_id' as 'The user's numeric ID.' This adds basic semantic meaning beyond the schema's title 'User Id' and type 'integer', though it doesn't elaborate on format constraints (e.g., valid ranges) or where to obtain the ID.
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 action ('Delete') and target ('a user from the company'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling deletion tools like 'delete_project_user' (which doesn't exist in the list) or 'delete_user', though the 'company' context provides some distinction.
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. The description doesn't mention prerequisites (e.g., user must exist, permissions required), consequences (e.g., data loss, access revocation), or related tools like 'create_user' or 'update_user' for user management workflows.
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 burden for behavioral disclosure. It states this is a deletion operation but provides no information about permissions required, whether deletion is permanent/reversible, what happens to associated data, or any rate limits. For a destructive operation with zero annotation coverage, this is a significant gap in behavioral transparency.
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 efficiently structured with a clear purpose statement followed by parameter documentation. The two-sentence format is appropriately concise, though the parameter documentation could be slightly more informative given the 0% schema coverage.
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 destructive operation with 2 parameters and no annotations, the description provides basic purpose and parameter information. The existence of an output schema means return values don't need explanation in the description. However, given the tool's destructive nature and lack of behavioral annotations, the description should provide more guidance about consequences and prerequisites to be truly 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 0%, so the schema provides no parameter documentation. The description adds basic parameter names and their purpose ('project_id: The project's numeric ID', 'logbook_id: The logbook ID'), which provides essential semantic information. However, it doesn't explain format constraints, valid ranges, or relationships between parameters beyond what's implied by their names.
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 action ('Delete') and resource ('a logbook'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'delete_logbook_entry' or 'delete_project', but the verb+resource combination is specific enough for basic understanding.
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 about when to use this tool versus alternatives like 'delete_logbook_entry' or 'delete_project', nor about prerequisites or consequences. The description only restates what's obvious from the tool name without contextual usage information.
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 burden for behavioral disclosure. It states 'Delete' which implies a destructive mutation, but doesn't clarify if deletion is permanent, requires authentication, has side effects, or what the output looks like. This is inadequate for a mutation tool with zero annotation coverage.
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. The parameter list is organized but could be more integrated. No wasted sentences, though it could be slightly more polished in structure.
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?
Given a destructive tool with 3 parameters (0% schema coverage), no annotations, but an output schema exists, the description is minimally adequate. It states the purpose and parameters but lacks behavioral details, usage context, and output explanation, relying on the output schema for return values.
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 0%, so the schema provides no parameter descriptions. The description lists the three parameters with brief labels ('The project's numeric ID', etc.), adding minimal semantic context. However, it doesn't explain format constraints, relationships between IDs, or example values, leaving significant gaps.
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 action ('Delete') and resource ('a logbook entry'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'delete_logbook' or 'delete_project_comment', which follow similar patterns for different resources.
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 alternatives. It doesn't mention prerequisites (e.g., needing specific permissions), what happens after deletion (e.g., irreversible), or when to choose other deletion tools like 'delete_logbook' for the entire logbook.
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 full burden. It states 'Delete' which implies a destructive mutation, but doesn't disclose behavioral traits like whether deletion is permanent/reversible, what permissions are required, or if there are rate limits. This is a significant gap for a mutation tool with zero annotation coverage.
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 front-loaded with the core purpose in the first sentence, followed by a brief parameter list. It avoids unnecessary verbosity, though the parameter section could be more integrated. Overall, it's efficient with minimal waste.
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?
Given the tool's complexity (destructive mutation with 2 parameters), lack of annotations, and 0% schema coverage, the description is incomplete. It doesn't cover behavioral aspects like side effects or error conditions. However, the presence of an output schema (not detailed here) might mitigate some gaps, keeping it at a minimally adequate level.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by naming the parameters ('project_id', 'comment_id') and stating they are numeric IDs, but doesn't explain format, sourcing, or validation rules. This partially compensates but leaves gaps, warranting a baseline score.
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 action ('Delete') and target ('a project comment'), which is specific and unambiguous. However, it doesn't differentiate from sibling tools like 'delete_task_comment' or 'delete_project_component', which would require more specificity about what distinguishes a project comment from other deletable entities.
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 alternatives. It doesn't mention prerequisites (e.g., needing proper permissions), exclusions, or related tools like 'get_project_comments' for context. This leaves the agent without usage context beyond the basic action.
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 full burden. 'Remove' implies a destructive mutation, but the description doesn't disclose whether this is reversible, what permissions are required, what happens to associated data, or what the response looks like. For a deletion tool with zero annotation coverage, this is a significant gap in behavioral disclosure.
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 efficiently structured with a clear purpose statement followed by parameter explanations. Both sentences earn their place by providing essential information. However, the 'Args:' section formatting is slightly redundant with the schema but still adds value given the 0% schema coverage.
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?
Given that there's an output schema (which handles return values), no annotations, and only 2 parameters with basic semantics covered, the description is minimally adequate. However, for a destructive operation with no safety annotations, it should ideally include more about consequences, permissions, or error conditions 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?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics for both parameters ('project's numeric ID' and 'component-in-project ID'), which helps understand what each ID represents. However, it doesn't provide format details, constraints, or examples, leaving some ambiguity about valid values.
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 action ('Remove') and target ('a component from a project'), providing specific verb+resource. It distinguishes from siblings like 'delete_project' (whole project) and 'delete_project_tag' (different resource), though not explicitly. However, it doesn't fully differentiate from 'delete_project_component' vs 'delete_project_comment' beyond the resource name.
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 like 'delete_project' or 'delete_project_tag'. The description provides basic function but no context about prerequisites, permissions needed, or when this operation is appropriate versus other deletion operations in the sibling list.
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 burden but only states the action ('Delete') without disclosing behavioral traits like whether deletion is permanent, requires specific permissions, affects related data (e.g., comments), or has confirmation steps. It misses critical context for a destructive operation.
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 action, followed by a simple parameter list. It avoids unnecessary words, though the 'Args' formatting is slightly redundant given the schema. Overall, it's efficient but could be more integrated.
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 destructive tool with no annotations, 0% schema coverage, and an output schema (implied by 'Has output schema: true'), the description is incomplete. It covers the basic action and parameter but lacks behavioral details, error handling, or output expectations, leaving gaps for safe agent use.
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 description includes an 'Args' section that names the parameter ('task_id'), but schema description coverage is 0%, and it doesn't add meaning beyond the schema (e.g., format examples, source of ID, or validation rules). With one parameter and no schema descriptions, baseline is 3 as it minimally documents the parameter.
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 verb ('Delete') and resource ('a task'), making the purpose unambiguous. It distinguishes from siblings like 'delete_project' or 'delete_task_comment' by specifying the task resource, though it doesn't explicitly contrast with them.
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 (e.g., 'update_task' for marking as completed vs. deletion, or 'delete_project' for broader removal). The description lacks context about prerequisites, permissions, or irreversible consequences, offering minimal usage direction.
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 full burden. It states the tool performs a deletion (destructive action) but doesn't disclose behavioral traits like whether deletion is permanent, requires authentication, has rate limits, or what happens on success/failure. The mention of 'Args' adds some structure but no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose in the first sentence, followed by a structured 'Args' section. It's appropriately sized with no redundant information, though the 'Args' labeling is slightly informal compared to standard MCP conventions.
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?
Given the tool has an output schema (not provided in details), the description doesn't need to explain return values. However, as a destructive operation with no annotations and 2 parameters, the description lacks completeness in behavioral context (e.g., permissions, side effects) and parameter details, making it adequate but with clear 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 0%, so the schema provides no parameter descriptions. The description adds basic semantics by naming the parameters ('task_id', 'comment_id') and indicating they are IDs, but doesn't explain format, constraints, or examples. This partially compensates but leaves gaps, meeting the baseline for minimal documentation.
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 action ('Delete a comment from a task') with specific resources (comment, task). It distinguishes from siblings like 'delete_project_comment' by specifying 'task' context, but doesn't explicitly contrast with other deletion tools like 'delete_task' or 'delete_project_comment' beyond the resource name.
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 is provided. The description doesn't mention prerequisites (e.g., needing specific permissions), error conditions, or when other tools like 'delete_project_comment' might be more appropriate. It only states the basic function without context.
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 burden for behavioral disclosure. While 'Disable' implies a state change (likely from enabled to disabled), it doesn't clarify if this is reversible, what permissions are required, whether it affects alert history, or what the expected outcome is. For a mutation tool with zero annotation coverage, this is insufficient.
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 appropriately brief with a clear purpose statement followed by parameter documentation. The two-sentence structure is efficient, though the parameter documentation could be integrated more smoothly rather than as a separate 'Args:' section.
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 single-parameter mutation tool with no annotations but with an output schema, the description provides basic purpose and parameter information. However, it lacks important context about behavioral implications, relationships to sibling tools, and expected outcomes that would help an agent use it 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?
Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds the minimal parameter documentation ('alert_id: The alert ID'), which explains what the parameter represents. However, it doesn't provide format details, validation rules, or examples that would be helpful for an agent.
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 action ('Disable') and resource ('an alert'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling 'enable_alert' tool, which would be helpful context for an agent choosing between them.
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 about when to use this tool versus alternatives like 'delete_alert' or 'enable_alert'. The description only states what the tool does, not when it should be selected over other alert management tools.
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. While 'Get details' implies a read-only operation, it doesn't specify authentication requirements, rate limits, error conditions, or what 'details' include. The description lacks critical behavioral context needed for safe and effective use.
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 appropriately concise with two sentences: a clear purpose statement followed by parameter documentation. It's front-loaded with the main intent. However, the 'Args:' section could be integrated more smoothly, and there's some redundancy in stating the parameter name twice.
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?
Given the tool has an output schema (which handles return values), a single parameter, and no annotations, the description is minimally adequate. It states the purpose and parameter meaning but lacks usage guidelines, behavioral context, and differentiation from siblings. For a simple read operation, it meets basic needs but leaves significant gaps for an agent to infer correct usage.
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 0%, so the schema provides no parameter descriptions. The description adds minimal value: it states 'function_id: The analysis function identifier,' which clarifies the parameter's purpose but doesn't explain format, constraints, or where to obtain valid IDs. This partially compensates for the schema gap but remains insufficient for full understanding.
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 purpose: 'Get details of a specific analysis function.' It uses a specific verb ('Get') and resource ('analysis function'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_analytics_functions' or 'get_analytics_instance', which could cause confusion about when to use each.
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 alternatives. With many sibling tools like 'get_analytics_functions' (plural) and 'get_analytics_instance', an agent wouldn't know whether this is for retrieving metadata about analysis functions versus their instances or results. No prerequisites, exclusions, or comparison context is 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 full burden. It mentions pagination parameters (page, per_page) which implies a paginated response, but doesn't disclose important behavioral traits like whether this is a read-only operation, what authentication is required, rate limits, error conditions, or what happens when parameters are null/default. The description is minimal and leaves critical behavior unspecified.
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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient with minimal waste, though the parameter explanations could be more integrated rather than listed separately.
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?
Given that an output schema exists (which should document return values), the description doesn't need to explain return format. However, for a tool with 3 parameters, 0% schema description coverage, and no annotations, the description provides basic purpose and parameter semantics but lacks important context about authentication, error handling, pagination behavior with null values, and differentiation from sibling tools.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantics for all three parameters (project_id, page, per_page), explaining what each represents. However, it doesn't provide format details (e.g., numeric ID format), constraints (e.g., valid page ranges), or explain what happens with null/default values for page/per_page, leaving gaps in understanding.
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 verb 'Get' and resource 'all analytics instances in a project', making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'get_analytics_instance' (singular) or 'get_analytics_instance_status', leaving some ambiguity about when to use this list tool versus individual instance tools.
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 alternatives. With siblings like 'get_analytics_instance' (singular), 'get_analytics_instances' (plural), and 'get_analytics_instance_status', there's clear potential for confusion, but the description offers no comparison or context about appropriate use cases.
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 full burden. It implies a read-only operation ('Get'), but doesn't disclose behavioral traits such as authentication needs, rate limits, error handling, or what 'attribute definitions' entail (e.g., format, scope). This is inadequate for a tool with no annotation coverage.
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 appropriately sized and front-loaded with the main purpose in the first sentence. The Args section is structured but could be more integrated. There's no wasted text, though it could be slightly more informative without losing 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?
Given 1 parameter with 0% schema coverage and an output schema exists, the description is minimally adequate. It explains the tool's purpose and parameter role but lacks behavioral context and usage guidance. With output schema handling return values, the description doesn't need to cover outputs, but overall completeness is limited.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by explaining 'component_id' as 'The component definition ID', which clarifies the parameter's role but lacks details like format constraints or examples. This partially compensates but leaves gaps.
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 action ('Get all attribute definitions') and resource ('for a component type'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_component_attributes' or 'get_component_pin_definitions', which appear related but have different scopes.
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 like 'get_component_attributes' or 'get_component_pin_definitions'. The description only states what it does without context or prerequisites, leaving the agent to infer usage.
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. It states the tool is a 'Get' operation, implying it is read-only, but does not specify any behavioral traits such as permissions required, rate limits, pagination, or what happens if the component_id is invalid. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 concise and well-structured, with a clear purpose statement followed by parameter details in a separate section. There is no unnecessary information, and it is front-loaded with the main functionality. It could be slightly improved by integrating the parameter explanation more seamlessly, but it is efficient overall.
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?
Given that there is an output schema (as indicated by context signals), the description does not need to explain return values. However, with no annotations, one parameter, and low schema coverage, the description provides basic purpose and parameter semantics but lacks usage guidelines and behavioral details. It is adequate for a simple read tool but has clear gaps in completeness.
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 description includes an 'Args' section that explains the 'component_id' parameter as 'The component definition ID.' This adds meaning beyond the input schema, which has 0% description coverage and only provides a title and type. However, with only one parameter, the baseline is high, and the explanation is minimal, so it meets but does not exceed basic expectations.
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 purpose: 'Get all pins and their attributes for a component type.' It specifies the verb ('Get'), resource ('pins and their attributes'), and scope ('for a component type'). However, it does not explicitly distinguish this tool from its sibling 'get_component_pins', which appears to be a similar tool, so it misses full differentiation.
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 alternatives. It does not mention any prerequisites, exclusions, or related tools like 'get_component_pins' from the sibling list. The only context is the parameter explanation, which is insufficient for usage decisions.
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. It states the tool retrieves data ('Get'), implying it's a read operation, but doesn't clarify aspects like permissions required, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its behavior.
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 concise and well-structured: a clear purpose statement followed by parameter explanations. There's no wasted language, and it's front-loaded with the main action. However, the lack of usage guidelines or behavioral details means it could be more informative without sacrificing brevity.
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?
Given that there's an output schema (which handles return values), the description doesn't need to explain outputs. However, with no annotations and low schema coverage, it should compensate more by detailing usage context and behavioral traits. It adequately covers the basic purpose and parameters but falls short on guidelines and transparency, making it minimally viable.
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 description coverage is 0%, meaning parameters are undocumented in the schema. The description adds basic semantics by explaining 'project_id: The project's numeric ID' and 'cip_id: The component-in-project ID,' which clarifies what these IDs represent. However, it doesn't provide details like valid ranges or examples, leaving some ambiguity.
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 purpose: 'Get all pin mappings for a component in a project.' It specifies the verb ('Get') and resource ('pin mappings for a component in a project'), making the action clear. However, it doesn't explicitly differentiate from sibling tools like 'get_component_pin_definitions' or 'map_component_pin', which could cause confusion about 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as whether the component must exist in the project, or compare it to related tools like 'get_component_pin_definitions' (which might define pins) or 'map_component_pin' (which might create mappings). This lack of context could lead to misuse.
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. It only states what the tool does ('Get analytics results') without describing any behavioral traits such as permissions required, rate limits, response format, pagination, or whether it's a read-only operation. For a tool with no annotation coverage, this is a significant gap in transparency.
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 appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by a parameter list. There's no unnecessary verbosity. However, the parameter explanations are very brief and could be more informative, slightly reducing efficiency.
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 the complexity (4 parameters, 2 required), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'analytics results' entail, how they're returned, or any behavioral aspects like error handling. For a tool with no structured support, this leaves significant gaps for an agent to use it 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?
Schema description coverage is 0%, so the schema provides no parameter descriptions. The description lists the parameters with brief explanations (e.g., 'The component-in-project ID'), which adds some meaning beyond the bare schema. However, it doesn't fully compensate for the coverage gap—it lacks details on formats, constraints, or examples for parameters like 'units_system' and 'currency_system', which are nullable strings.
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 purpose: 'Get analytics results for a specific component in a project.' It specifies the verb ('Get'), resource ('analytics results'), and scope ('specific component in a project'). However, it doesn't explicitly differentiate from sibling tools like 'get_analytics_instance_result' or 'get_analytics_components_kpi', which appear related, so it doesn't fully achieve sibling differentiation.
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 alternatives. It doesn't mention prerequisites, context, or exclusions, nor does it reference any of the many sibling tools that might be related (e.g., other analytics or component tools). This leaves the agent with no usage context beyond the basic purpose.
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 the full disclosure burden but offers only 'Get details' implying read-only access. It lacks information on auth requirements, what specific details are returned, rate limits, or error handling (e.g., invalid app_id).
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 first sentence delivers the core purpose immediately. The Args section is structured and readable, though technically redundant with the JSON schema (which has no descriptions). No fluff, but the docstring format consumes space that could elaborate on semantics.
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?
Adequate for a single-parameter retrieval tool without output schema, providing just enough to invoke correctly. However, given the domain complexity (app vs instance distinction among siblings), the description lacks critical context needed to select the correct tool from the suite.
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?
Compensates for 0% schema description coverage by identifying `app_id` as 'The controls app identifier' in the Args section. However, it provides minimal value beyond the parameter name itself—no format specifications, examples, or where to obtain valid IDs are given.
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?
States a clear verb ('Get') and resource ('details of a specific controls app'), establishing the retrieval pattern. However, it fails to differentiate from sibling `get_controls_apps` (list vs single) or clarify the relationship between a 'controls app' and 'controls instance' given the presence of sibling instance tools.
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?
Provides no guidance on when to use this singular retrieval versus the plural `get_controls_apps`, nor when to query an app versus an instance. No prerequisites, error conditions, 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 of behavioral disclosure. It only states 'Get details,' which implies a read-only operation but does not specify authentication needs, rate limits, error conditions, or what 'details' include. This is inadequate for a tool with no annotation coverage.
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 concise and well-structured: a brief purpose statement followed by parameter explanations. It uses bullet points for parameters, making it easy to scan. However, the parameter explanations could be more detailed given the lack of schema descriptions.
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?
Given that there is an output schema (which handles return values), the description's main gaps are in usage guidelines and behavioral transparency. It covers the basic purpose and parameters but lacks context on when to use it, error handling, or performance traits. This is minimally adequate but with clear 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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics: it explains 'project_id' as 'The project's numeric ID' and 'datapoint_id' as 'The datapoint identifier (hash key or alternate key).' This clarifies the nature of the IDs but does not fully compensate for the coverage gap, as it lacks format examples or constraints.
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 purpose: 'Get details about a specific datapoint.' It uses a specific verb ('Get') and resource ('datapoint'), but does not differentiate from sibling tools like 'get_project_datapoints' or 'get_datapoint_timeseries', which also retrieve datapoint-related information. The purpose is clear but lacks sibling differentiation.
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 alternatives. It does not mention prerequisites, context, or exclusions. For example, it does not clarify if this is for retrieving metadata versus timeseries data, or when to use it over 'get_project_datapoints' for listing multiple datapoints.
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 states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication needs, rate limits, pagination, error conditions, or what the output contains. For a tool with no annotation coverage, this is a significant gap in transparency.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are brief and directly relevant. There's no wasted text, though the structure could be slightly improved by integrating parameter details more seamlessly rather than as a separate 'Args:' section.
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?
Given that there's an output schema (which handles return values), no annotations, and low schema coverage, the description is minimally complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidance. For a simple read tool with output schema support, it's adequate but has clear gaps in transparency and guidelines.
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 0%, so the schema provides no descriptions for parameters. The description adds minimal semantics by naming the parameters ('project_id', 'datapoint_id') and briefly stating their purpose ('The project's numeric ID', 'The datapoint identifier'), but doesn't elaborate on formats, constraints, or examples. This partially compensates but leaves gaps, aligning with the baseline 3 when schema coverage is low.
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 verb ('Get') and resource ('usage information for a datapoint') with a clarifying parenthetical ('where it's referenced'). It distinguishes from obvious siblings like 'get_datapoint' (which retrieves the datapoint itself) and 'get_datapoint_timeseries' (which retrieves time-series data). However, it doesn't explicitly differentiate from all sibling 'get_' tools, keeping it at 4 rather than 5.
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. The description doesn't mention prerequisites, typical use cases, or what 'usage information' entails (e.g., references in logs, alerts, or components). It simply states what it does without context for selection among many 'get_' tools.
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 full burden. It implies a read operation ('Get') but doesn't disclose behavioral traits such as authentication needs, rate limits, pagination, or what 'personal favorite' entails (e.g., user-specific vs. project-wide). This leaves significant gaps for an agent to understand how to use it effectively.
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 front-loaded with the main purpose in the first sentence, followed by a concise Args section. It avoids unnecessary words, though the structure could be slightly improved by integrating the parameter explanation more seamlessly.
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?
Given that there is an output schema (which reduces the need to describe return values) and no annotations, the description is minimally adequate. However, for a tool with 1 parameter and 0% schema coverage, it should provide more context about the 'favorite' concept and usage scenarios to be fully helpful.
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 0%, but the description adds the parameter 'project_id' with a brief explanation ('The project's numeric ID'). This provides basic semantics beyond the schema's title 'Project Id', but it doesn't clarify why this parameter is required or how it affects the output, leaving room for improvement.
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 verb 'Get' and the resource 'all personal favorite datapoints', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'get_datapoint' or 'get_project_datapoints' by explaining what makes 'favorite' datapoints distinct.
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 like 'get_datapoint' or 'get_project_datapoints'. The description only states what it does without context about prerequisites, timing, or comparisons to other tools in the list.
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 full burden. It implies a read operation ('Get') but doesn't disclose behavioral traits like whether it returns all logbooks at once or paginates, what happens if the project_id is invalid, or if authentication/permissions are required. This leaves significant gaps for a tool that likely interacts with project data.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The Args section is clear but could be integrated more seamlessly. There's no wasted text, though it could be slightly more polished in structure.
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?
Given the tool's low complexity (1 parameter) and the presence of an output schema (which handles return values), the description is somewhat complete but lacks behavioral context. Without annotations, it should ideally mention more about usage constraints or error cases to fully guide an agent, but the output schema reduces the burden.
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 description adds minimal semantics: it clarifies that 'project_id' is 'The project's numeric ID', which is slightly more informative than the schema's 'Project Id' title. However, with 0% schema description coverage and only 1 parameter, this doesn't fully compensate for the lack of schema details, but it meets the baseline for minimal parameter info.
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 verb 'Get' and resource 'all logbooks in a project', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_logbook' (singular) or 'create_logbook', leaving room for ambiguity about when to use this versus those 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 is provided on when to use this tool versus alternatives like 'get_logbook' (singular) or 'create_logbook'. The description only states what it does, not when it's appropriate or what prerequisites might exist (e.g., needing a valid project_id).
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 burden for behavioral disclosure. It only states what the tool does ('Get all saved plot views') without mentioning any behavioral traits like whether this is a read-only operation, if it requires specific permissions, what format the results come in, or if there are pagination/rate limits. This leaves significant gaps for a tool that presumably returns data.
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 efficiently structured with a clear purpose statement followed by parameter documentation. Both sentences earn their place by providing essential information without redundancy. The only minor improvement would be integrating the parameter info more seamlessly rather than as a separate 'Args' section.
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?
Given that an output schema exists (which handles return values), the description covers the basic purpose and parameter. However, for a data retrieval tool with no annotations, it lacks important context about behavioral aspects like permissions, response format details beyond the schema, or error conditions. The presence of an output schema raises the baseline but doesn't fully compensate for missing behavioral transparency.
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 description includes an 'Args' section that documents the single parameter 'project_id' with a brief explanation ('The project's numeric ID'). With 0% schema description coverage, this adds meaningful context beyond the schema's type information. However, it doesn't provide additional details like valid ID ranges or examples, keeping it at baseline adequacy.
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 action ('Get all saved plot views') and the target resource ('for a project'), providing specific verb+resource pairing. However, it doesn't explicitly differentiate from sibling tools like 'create_plot_view' or 'delete_plot_view' beyond the obvious action difference, which prevents a perfect score.
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 alternatives. There are no explicit statements about when/when-not to use it, nor references to sibling tools like 'get_project_components' or 'get_project_datapoints' that might serve similar purposes for different data types.
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 full burden for behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify authentication requirements, rate limits, error conditions, or what 'details' encompass (e.g., basic metadata vs. full configuration). For a tool with no annotation coverage, this leaves significant behavioral gaps.
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 appropriately concise with two sentences: a clear purpose statement and a parameter explanation. It's front-loaded with the main functionality. The structure is efficient, though the parameter documentation could be integrated more seamlessly rather than as a separate 'Args:' section.
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?
Given the tool's low complexity (single parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema coverage, it should provide more context about behavioral aspects like permissions or error handling to be fully complete for agent use.
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 0%, so the schema provides no parameter documentation. The description adds minimal semantics by specifying 'project_id: The project's numeric ID,' clarifying the parameter's purpose and type. However, it doesn't explain format constraints, valid ranges, or where to obtain this ID, leaving some ambiguity.
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 purpose with a specific verb ('Get') and resource ('a project's details'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_project_comments' or 'get_project_components', which also retrieve project-related information but focus on specific aspects rather than general details.
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 alternatives. With many sibling tools like 'get_project_comments' or 'get_project_tasks' that retrieve specific project data, there's no indication whether this tool returns comprehensive details or if it should be preferred over more targeted queries. The only implied usage is needing a project ID.
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 burden for behavioral disclosure. It mentions pagination parameters which implies a list operation with potential result limits, but doesn't describe what 'alerts' consist of, whether the operation is safe/read-only, authentication requirements, rate limits, error conditions, or the structure of returned data. The description is minimal beyond stating the basic operation.
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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence serves a purpose with minimal waste. The formatting with 'Args:' section makes it scannable, though the parameter explanations could be slightly more informative.
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?
Given that there's an output schema (which handles return values), no annotations, and moderate complexity (3 parameters with 0% schema coverage), the description provides the minimum viable information. It states what the tool does and documents parameters, but lacks behavioral context, usage guidance, and richer parameter semantics that would be helpful for an AI 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 description coverage is 0%, so the description must compensate. It provides parameter names and brief explanations ('The project's numeric ID', 'Page number', 'Items per page'), which adds basic semantic meaning beyond the schema's type information. However, it doesn't explain valid ranges, constraints, or practical usage details for the pagination parameters (like typical page sizes or what 'null' means for defaults).
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 action ('Get all alerts') and resource ('configured in a project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from potential siblings like 'get_analytics_instance' or 'get_controls_instance' that might also retrieve alert-related data, though those appear to be for different resource types.
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 alternatives. While there are sibling tools like 'create_threshold_alert', 'delete_alert', 'disable_alert', and 'enable_alert' that manage alerts, the description doesn't mention these relationships or provide context about when retrieval versus modification is appropriate.
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 full burden. It mentions pagination and filtering, which hints at behavior, but doesn't disclose critical traits like rate limits, authentication needs, error handling, or whether it's read-only (implied by 'Get' but not explicit). For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.
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 front-loaded with the core purpose, followed by a structured Args section. It's efficient with minimal waste, though the Args formatting is slightly verbose for a simple list. Every sentence adds value, and the structure aids readability.
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?
Given 4 parameters with 0% schema coverage and no annotations, the description provides basic parameter info but lacks depth on behavior, usage context, or output details. The presence of an output schema mitigates the need to explain return values, but overall completeness is moderate—adequate for a simple retrieval tool but with clear gaps in guidance and transparency.
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 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'Filter string for datapoint names'), adding some semantics beyond the bare schema. However, it doesn't detail format constraints (e.g., filter syntax), value ranges, or default behaviors for nullable parameters, leaving room for ambiguity.
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 verb ('Get') and resource ('all datapoints in a project'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_datapoint' (singular) or 'get_favorite_datapoints', which might retrieve different subsets or types of datapoints.
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. With many sibling tools related to datapoints (e.g., get_datapoint, get_favorite_datapoints, get_datapoint_timeseries), the description lacks context about prerequisites, typical use cases, or comparisons to other retrieval methods.
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 full burden for behavioral disclosure. It implies a read operation ('Get'), but doesn't specify if it's safe, requires permissions, has rate limits, or describes output format. The description adds minimal context beyond the basic action, failing to compensate for lack of annotations, resulting in a score of 2.
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 appropriately sized and front-loaded, with the main purpose stated first in a clear sentence, followed by a concise parameter explanation. There's no wasted text, but the structure could be slightly improved by integrating the Args more seamlessly, keeping it efficient but not perfect.
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?
Given the tool's low complexity (single parameter) and the presence of an output schema (which handles return values), the description is minimally adequate. It covers the basic action and parameter, but lacks behavioral details and usage guidelines. With no annotations, it should do more to be fully complete, scoring 3 as the minimum viable.
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 0%, but the description includes an 'Args' section that documents the single parameter 'project_id' as 'The project's numeric ID.' This adds meaning beyond the schema's basic type, providing semantic context. However, it doesn't detail format constraints or examples, so it meets the baseline of 3 without fully compensating for low coverage.
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 purpose as 'Get all setpoints in a project,' specifying the verb 'Get' and resource 'setpoints' with scope 'in a project.' It distinguishes from siblings like 'get_setpoint_status' (status vs. all setpoints) and 'write_setpoint' (write vs. read), though not explicitly. However, it lacks explicit sibling differentiation, keeping it at 4 rather than 5.
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 alternatives. It doesn't mention prerequisites, context, or exclusions, such as when to prefer 'get_setpoint_status' for status checks or 'write_setpoint' for modifications. This leaves the agent without usage direction, scoring 2 for minimal guidance.
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 full burden. It mentions pagination parameters but doesn't disclose behavioral traits like whether this is a read-only operation, what permissions are required, how results are ordered, error handling, or rate limits. The description adds minimal context beyond the basic operation.
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 appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are listed clearly, though the structure could be more integrated. There's minimal waste, but it lacks flow between the purpose and parameter sections.
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?
Given 3 parameters with 0% schema coverage and no annotations, the description is moderately complete but has gaps. It covers the basic operation and parameters but lacks behavioral context, error details, and output explanation (though an output schema exists, reducing the need for return value description). For a list tool with pagination, more guidance on usage and constraints would be beneficial.
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 0%, so the description must compensate. It lists all three parameters with brief explanations, adding meaning beyond the schema's titles. However, it doesn't provide format details (e.g., numeric ID specifics), default behaviors for null page/per_page, or constraints, leaving gaps in parameter understanding.
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 purpose as 'Get all tasks in a project' with a specific verb ('Get') and resource ('tasks in a project'). It distinguishes from siblings like 'get_task' (singular) and 'create_task', but doesn't explicitly differentiate from other list operations like 'get_project_comments' or 'get_project_components' beyond the resource type.
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. The description doesn't mention prerequisites, context for pagination, or compare it to other task-related tools like 'get_task' (singular) or 'assign_task'. Usage is implied by the name and description alone.
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. It states this is a 'Get' operation, implying it's read-only, but doesn't confirm this explicitly. It doesn't describe error conditions (e.g., invalid project_id), rate limits, authentication requirements, or what happens if the project lacks location data. The description adds minimal behavioral context beyond the basic operation.
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 appropriately concise and well-structured. The first sentence clearly states the purpose, followed by an 'Args:' section that lists parameters with brief explanations. There's no unnecessary information, and it's front-loaded with the core functionality. However, the 'Args:' formatting could be slightly more polished, but it remains efficient.
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?
Given that there's an output schema (which handles return values) and no annotations, the description is moderately complete. It covers the basic purpose and parameters but lacks usage guidelines, detailed behavioral context, and differentiation from siblings. For a tool with 2 parameters and 0% schema coverage, the description does the minimum to be functional but leaves significant gaps in guiding an AI agent effectively.
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 0%, so the schema provides no parameter descriptions. The description adds some value by explaining 'project_id: The project's numeric ID' and 'units_system: Unit system (e.g., 'SI')', giving basic semantics for both parameters. However, it doesn't clarify the format of 'units_system' beyond an example (e.g., are other values like 'imperial' allowed?), and it doesn't explain the default behavior when 'units_system' is null. This partially compensates for the schema gap but leaves ambiguities.
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 purpose: 'Get current weather for a project's location.' It specifies the verb ('Get') and resource ('weather for a project's location'), making it immediately understandable. However, it doesn't explicitly differentiate from its sibling 'get_project_weather_forecast', which suggests a similar weather-related function but for forecasts rather than current conditions.
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 alternatives. It doesn't mention the sibling 'get_project_weather_forecast' or explain the difference between current weather and forecast data. There's also no information about prerequisites, such as whether the project must exist or have a valid location configured.
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. It states the tool retrieves a forecast but lacks details on permissions, rate limits, data freshness, or response format. While 'Get' implies a read-only operation, it doesn't confirm safety or describe potential errors, leaving significant gaps for a tool with no annotation coverage.
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 front-loaded with the core purpose, followed by parameter explanations. It uses two sentences efficiently, with no wasted words. However, the parameter section could be more integrated into the main description for better flow, but overall it's appropriately sized and 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?
Given the tool's moderate complexity (2 parameters, no annotations, but has an output schema), the description is minimally adequate. It explains what the tool does and the parameters but misses behavioral context and usage guidelines. The output schema likely covers return values, reducing the need for that in the description, but gaps remain in transparency and guidelines.
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 0%, so the schema provides no parameter descriptions. The description adds basic semantics: 'project_id: The project's numeric ID' and 'units_system: Unit system (e.g. 'SI')'. This clarifies the purpose of both parameters but lacks details like valid unit values or project ID constraints. It compensates partially but not fully for the schema gap.
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 purpose: 'Get weather forecast for a project's location.' It specifies the verb ('Get') and resource ('weather forecast'), and distinguishes it from siblings like 'get_project_weather' (which likely provides current weather). However, it doesn't explicitly differentiate from all potential weather-related tools beyond the sibling list context.
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 alternatives. It doesn't mention prerequisites, such as needing a valid project ID, or contrast it with other weather tools like 'get_project_weather'. Usage is implied only through the tool name and parameters, with no explicit context or exclusions provided.
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, so the description carries full behavioral burden. It mentions pagination parameters but fails to disclose default behaviors when null (likely returns all or first page), rate limits, permissions required, or that results are paginated.
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 Args-section format is functional and wastes no words. The single-line purpose statement is front-loaded. The structure is slightly dry (docstring-style) but appropriate for the technical content.
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?
Adequate for a simple list retrieval with existing output schema. However, given zero schema descriptions, the description should elaborate on pagination defaults (e.g., whether null returns all items) and 'realm' scope definition.
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?
With 0% schema description coverage, the description minimally compensates by labeling 'page' as 'Page number' and 'per_page' as 'Items per page'. This adds meaning beyond the schema titles but lacks details on valid ranges, default behavior, or maximum values.
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?
States specific verb ('Get') and resource ('companies in the realm'), with 'all' distinguishing it from sibling 'get_company' (singular). However, it doesn't explain what constitutes a 'realm' or explicitly contrast with the singular variant.
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?
Provides no guidance on when to use this versus 'get_company' or other filtering alternatives. The pagination arguments imply bulk retrieval, but prerequisites or selection criteria are absent.
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. It states it 'Get[s] all projects' but doesn't clarify if this is a read-only operation, whether it requires authentication, how pagination works (beyond listing parameters), or what happens on errors. For a tool with pagination parameters and no annotation coverage, this leaves significant behavioral gaps.
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 appropriately concise and front-loaded, with the core purpose stated first followed by parameter details. There's no wasted text, and the structure is clear. It could be slightly improved by integrating parameter explanations more seamlessly, but it's efficient overall.
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?
Given the tool's low complexity (2 parameters, no nested objects) and the presence of an output schema (which reduces the need to describe return values), the description is somewhat complete but has gaps. It covers the basic action and parameters but lacks behavioral context (e.g., pagination behavior, error handling) and usage guidelines, making it minimally adequate but not fully helpful.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by listing 'page' and 'per_page' with brief labels ('Page number' and 'Items per page'), which clarifies their basic purpose. However, it doesn't explain default values, valid ranges, or how null values are handled, leaving key details undocumented.
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 purpose: 'Get all projects in the realm.' It uses a specific verb ('Get') and resource ('projects in the realm'), making the function unambiguous. However, it doesn't explicitly distinguish itself from sibling tools like 'get_project' or 'get_realm_companies', which would be needed for a perfect score.
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 alternatives. It doesn't mention sibling tools like 'get_project' (for a single project) or 'get_realm_companies' (for other realm entities), nor does it specify prerequisites or context for usage. The lack of comparative or contextual advice limits its utility for an AI agent.
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 provided, so description carries full disclosure burden. While 'Get' implies read-only safety, the description lacks details on error behavior (task not found), what specific details are returned, or side effects. Minimal behavioral context given.
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?
Front-loaded action statement is efficient. The Args section uses standard docstring format which is appropriate given the schema's 0% description coverage, though it adds minimal new information. No verbose 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?
Given the output schema exists (per context signals), return value description is unnecessary. For a simple single-parameter getter, the description is minimally adequate but misses error condition documentation and relationship to sibling list operations.
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%, requiring description compensation. The Args section provides minimal semantic value by labeling the parameter as 'The task ID', confirming integer usage. However, it omits format constraints, valid ranges, or provenance (where to obtain valid task IDs). Just meets minimum threshold.
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?
Clear verb 'Get' and resource 'details of a task' establishes the read operation. However, it fails to differentiate from sibling 'get_project_tasks' (which retrieves multiple tasks), risking incorrect selection when the agent needs to fetch tasks by project versus fetching a specific task by ID.
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 provided on when to use this single-task retrieval versus 'get_project_tasks' for listing. No prerequisites mentioned (e.g., that the task_id typically comes from a previous project tasks query).
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 the full burden of behavioral disclosure. It states the action ('Remove') but lacks details on permissions required, whether the operation is reversible, error conditions (e.g., if datapoint isn't favorited), or side effects. This is inadequate for a mutation tool with zero annotation coverage.
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 front-loaded with the core purpose in the first sentence, followed by a structured 'Args' section. It's appropriately sized with minimal fluff, though the parameter explanations could be more detailed given the low schema coverage.
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?
Given the tool's complexity (mutation with 2 parameters), no annotations, and an output schema (which reduces need to describe returns), the description is partially complete. It covers the basic action and parameters but lacks behavioral context, usage guidelines, and detailed parameter semantics, making it adequate but with clear 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 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that lists and briefly explains the two parameters ('project_id' and 'datapoint_id'), adding basic semantics. However, it doesn't specify formats (e.g., datapoint_id structure) or constraints, leaving gaps.
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 action ('Remove') and resource ('a datapoint from personal favorites'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'set_favorite_datapoint' or 'get_favorite_datapoints' beyond the obvious verb difference, missing explicit comparison.
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. It doesn't mention prerequisites (e.g., datapoint must already be favorited), exclusions, or relationships with sibling tools like 'set_favorite_datapoint' (for adding) or 'get_favorite_datapoints' (for listing).
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 the full burden of disclosure. It only adds the 'personal' scope (user-specific) but fails to describe mutation behavior, idempotency, error conditions, or what the output schema contains.
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 docstring format with Args section is structured and front-loaded with the primary action. No sentences are wasted, though the Args format is slightly unconventional for MCP descriptions (typically prose paragraphs).
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?
Given the output schema exists (per context signals), the description appropriately omits return value details. For a 2-parameter mutation tool, it covers the minimum but misses behavioral edge cases and sibling relationships that would aid agent selection.
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?
With 0% schema description coverage, the Args section compensates by adding basic semantics: project_id is 'numeric' and datapoint_id is an 'identifier'. However, it lacks constraint details, format specifications, or cross-parameter dependencies.
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 action ('Mark') and resource ('datapoint') with clear scope ('personal favorite'), distinguishing it from general project operations. However, it does not explicitly differentiate from siblings like remove_favorite_datapoint or get_favorite_datapoints.
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 (e.g., remove_favorite_datapoint), prerequisites (e.g., datapoint must exist), or preconditions (e.g., idempotency behavior if already favorited).
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. It states the tool triggers an instance to run, implying a write/mutation operation, but doesn't clarify permissions required, side effects (e.g., if it overrides schedules), rate limits, or what happens on success/failure. This is inadequate for a mutation tool with zero annotation coverage.
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 front-loaded with the core purpose in the first sentence, followed by parameter details. It avoids unnecessary words, but the parameter section could be integrated more seamlessly. Overall, it's efficient with minimal waste.
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?
For a mutation tool with no annotations, no output schema, and 2 parameters with 0% schema coverage, the description is incomplete. It lacks behavioral context (e.g., effects, errors), output details, and deeper parameter guidance. Given the complexity implied by siblings like 'get_analytics_instance_result', more completeness is needed.
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 0%, so the schema provides no parameter descriptions. The description adds minimal semantics by naming the parameters ('instance_id', 'project_id') and stating they are IDs, but doesn't explain their format, sourcing, or relationship (e.g., that the instance belongs to the project). This partially compensates but leaves gaps, warranting a baseline score.
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 action ('manually trigger') and resource ('analytics instance to run'), making the purpose understandable. It distinguishes from siblings like 'create_analytics_instance' or 'get_analytics_instance_status' by focusing on execution rather than creation or status checking. However, it doesn't explicitly differentiate from 'enable_analytics_instance', which might be a related operation.
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 alternatives like 'enable_analytics_instance' or 'get_analytics_instance_status'. It lacks context about prerequisites (e.g., whether the instance must be enabled or configured) or typical scenarios for manual triggering, leaving the agent without usage direction.
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 burden but offers minimal behavioral insight. It states the action is to 'unmap,' implying a mutation, but doesn't disclose permissions needed, side effects (e.g., if this affects data integrity), or response behavior. More context on what 'unmap' entails operationally would be helpful.
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 front-loaded with the core purpose in the first sentence, followed by a structured 'Args' section. It's appropriately sized with no redundant information, though the parameter descriptions could be more detailed without sacrificing 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?
Given the tool has an output schema (which handles return values), no annotations, and 3 parameters with 0% schema coverage, the description is minimally adequate. It covers the basic action and parameters but lacks behavioral details, usage context, and deeper parameter semantics, making it incomplete for optimal agent understanding.
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 0%, so the schema provides no parameter descriptions. The description includes an 'Args' section that lists and briefly identifies each parameter (e.g., 'project_id: The project's numeric ID'), adding basic meaning. However, it doesn't explain relationships between parameters (e.g., how cip_id relates to project_id) or provide examples, leaving gaps in understanding.
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 action ('Unmap') and target ('a pin from a component in a project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'map_component_pin' beyond the opposite action, missing an opportunity for clearer sibling distinction.
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 or any prerequisites. The description doesn't mention its sibling 'map_component_pin' for context, nor does it indicate what conditions must be met before unmapping (e.g., the pin must already be mapped).
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 burden for behavioral disclosure. While 'Update' implies a mutation operation, the description doesn't address critical behavioral aspects: whether this requires specific permissions, if changes are reversible, what happens when only some fields are provided, rate limits, or error conditions. The description merely restates the tool name without adding meaningful 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately concise with a clear header followed by parameter explanations. The structure is logical and front-loaded with the core purpose. However, the 'Args:' section formatting could be more integrated with the main description text.
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?
Given that this is a mutation tool with no annotations, 4 parameters (2 required), 0% schema coverage, but with an output schema present, the description is minimally adequate. The presence of an output schema means the description doesn't need to explain return values, but it should provide more behavioral context for a write operation. The description covers the basics but leaves significant gaps in usage and behavioral understanding.
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 description lists all 4 parameters with brief explanations, but with 0% schema description coverage, this only partially compensates. The explanations are minimal ('New description', 'New unit string') and don't provide format requirements, constraints, or the implications of null values. While better than nothing, this doesn't fully address the schema coverage gap.
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 action ('Update') and resource ('datapoint details'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other update tools in the sibling list (like update_project, update_task, update_analytics_instance), which prevents a perfect score.
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 alternatives. There's no mention of prerequisites, when this operation is appropriate, or what distinguishes it from other datapoint-related tools like delete_datapoint or get_datapoint. The agent must infer usage from the tool name alone.
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 full burden. 'Update a project's details' implies a mutation operation but doesn't disclose behavioral traits like required permissions, whether updates are partial or complete, what happens with null values, or error conditions. This leaves significant gaps for a mutation tool.
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 appropriately brief with a clear purpose statement followed by parameter documentation. The Args section is well-structured but could be more integrated with the main description. No wasted sentences, though the formatting could be slightly more polished.
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?
Given this is a mutation tool with no annotations but with an output schema (which handles return values), the description covers basic purpose and parameters adequately. However, it lacks important context about permissions, side effects, and error handling that would be needed for safe agent use.
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 0%, so the description must compensate. The Args section lists all three parameters (project_id, name, description) and indicates name and description can be null, adding meaningful semantics beyond the bare schema. However, it doesn't explain constraints like project_id format or name/description length limits.
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 verb ('Update') and resource ('a project's details'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other update tools like update_analytics_instance or update_controls_instance in the sibling list, which prevents a perfect score.
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 alternatives like create_project or delete_project, nor does it mention prerequisites or context for when updates are appropriate. The Args section documents parameters but doesn't constitute usage guidance.
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 full burden. 'Update a task' implies a mutation operation, but the description doesn't disclose any behavioral traits: no information about permissions required, whether changes are reversible, rate limits, error conditions, or what happens to unspecified fields. The mention of 'JSON string with fields to update' hints at partial updates but doesn't clarify behavior.
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 appropriately sized and front-loaded with the core purpose. The two-sentence structure with parameter explanations is efficient. However, the 'Args:' section formatting is slightly redundant with the schema but still concise overall.
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?
Given that there's an output schema (which handles return values), no annotations, and 2 parameters with 0% schema coverage, the description is moderately complete. It covers parameter semantics well but lacks behavioral context and usage guidance. For a mutation tool with no annotations, it should provide more about permissions, side effects, or error handling.
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?
Schema description coverage is 0%, so the description must compensate. It provides meaningful context for both parameters: 'task_id: The task ID' clarifies the identifier type, and 'task_data: JSON string with fields to update (title, description, status, etc.)' explains the format and provides examples of updatable fields. This adds substantial value beyond the bare schema.
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?
The description states 'Update a task' which is a clear verb+resource combination, but it's overly generic. It doesn't distinguish from sibling tools like 'update_project' or 'update_user' beyond specifying the resource type. The purpose is understandable but lacks specificity about what aspects of a task can be updated.
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 about when to use this tool versus alternatives. There's no mention of prerequisites (like needing an existing task), comparison to similar tools (like 'create_task' or 'delete_task'), or any contextual constraints. The agent must infer usage from the tool name alone.
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 provided. Description mentions 'logged-in user' indicating authentication scope, but fails to disclose mutation semantics: partial update behavior (both params nullable/optional), what null values do (clear vs unchanged), or output structure despite having an 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?
Efficient three-line structure with clear intent stated upfront. The 'Args:' block is somewhat unconventional for MCP but conveys parameter semantics concisely. No redundant text.
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?
Adequate for a 2-parameter tool with output schema covered elsewhere. Acceptable baseline coverage, though missing partial-update semantics and null-handling behavior that would complete the behavioral contract.
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 has 0% description coverage (only titles). Description compensates minimally by identifying parameters as 'New first name' and 'New last name', adding semantic value beyond schema titles. However, fails to explain the nullable anyOf types, default null behavior, or partial update capability.
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?
Clearly identifies the operation (Update) and target resource (logged-in user's details). Scope restriction to 'logged-in user' distinguishes from potential admin update tools. Deducted one point for not specifying that only name fields are updatable, leaving the 'details' scope vague.
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 versus create_user, nor does it mention that all parameters are optional (0 required) enabling partial updates. No prerequisites or error conditions 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a write operation, implying mutation, but doesn't address critical aspects like required permissions, whether it overwrites or appends data, rate limits, error handling, or what the output schema contains. This leaves significant gaps for an agent to understand the tool's behavior.
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 well-structured and efficient, with a clear purpose statement followed by parameter explanations. Both sentences add value without redundancy. It could be slightly more front-loaded by integrating the parameter details into the main flow, but overall it's concise and readable.
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?
Given the tool's complexity (a write operation with structured JSON input), the description covers the basics but lacks depth. It explains parameters and the action, but with no annotations and an unspecified output schema (though one exists), it misses behavioral context like side effects, error cases, or output format. For a mutation tool, this is minimally adequate but leaves room for improvement.
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 description includes an 'Args' section that explains both parameters: 'project_id' as a numeric ID and 'timeseries_data' as a JSON string with a specific structure. However, with 0% schema description coverage, the schema provides no additional details. The description compensates adequately by defining parameter purposes and the JSON format, but doesn't clarify constraints like valid value ranges or time formats.
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 action ('Write timeseries data') and target resource ('to datapoints in a project'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'write_setpoint' or 'delete_project_timeseries', which handle similar data operations but on different resources.
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 alternatives. It doesn't mention prerequisites (e.g., needing an existing project or datapoint), nor does it contrast with sibling tools like 'get_project_timeseries' (for reading) or 'delete_project_timeseries' (for removal).
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 disclosure burden but provides minimal behavioral context. No mention of permissions required, whether creation is synchronous, validation rules for the JSON config, or side effects.
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?
Brief and front-loaded. The Args section is necessary given zero schema coverage and efficiently delivers the required parameter semantics without redundancy.
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?
Inadequate for a creation tool with lifecycle implications (see siblings delete_analytics_instance, disable_analytics_instance). Missing: config structure details, relationship to update_analytics_instance, and whether output schema contains the created instance ID.
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?
Schema description coverage is 0%, requiring the description to compensate. It adds type context ('numeric ID', 'JSON string') for both parameters beyond the schema's titles, though instance_config lacks structural details.
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?
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 when/when-not guidance provided. Does not mention prerequisite steps (e.g., needing a project_id first) or distinguish from sibling tools like create_controls_instance or create_plot_view.
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 provided, so description carries full burden. 'Initial password' hints at temporary credentials but misses critical behavioral details: permissions required, idempotency/duplicate handling, whether welcome emails are sent, or what the output schema contains.
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?
Front-loaded purpose statement followed by structured Args block. No redundancy or waste. Slightly unusual formatting but clear and efficient.
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?
User creation is a high-permission operation with complex error conditions (duplicates, validation), yet the description lacks behavioral context. Output schema exists (reducing description burden for return values), but mutation semantics and company/realm distinctions remain under-documented.
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?
With 0% schema description coverage, the description compensates by documenting all 4 parameters in the Args block. Descriptions are minimal (e.g., 'First name' for first_name) but provide basic type semantics missing from the schema.
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?
States specific verb (Create) + resource (user) + scope (in the company). Distinguishes from realm-level siblings like get_realm_users via 'company' qualifier, but does not differentiate from update_user for existing users.
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 explicit guidance on when to use this versus update_user for existing users, or prerequisites like admin permissions. No alternatives or exclusions 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. While 'Get' implies a read-only operation, the description discloses nothing about data freshness, calculation triggers, caching behavior, or the structure of the returned overview.
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 appropriately front-loaded with the purpose statement followed by an Args section. No redundant text is present, though extreme brevity contributes to gaps in behavioral and contextual completeness.
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 the rich sibling tool context (many analytics KPI variants) and lack of output schema, the description fails to clarify what distinguishes a 'high-level overview' from component-level or aggregated KPIs, leaving tool selection ambiguous.
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?
With 0% schema description coverage, the description compensates by documenting the sole parameter ('project_id: The project's numeric ID'). While minimal, this provides the necessary semantic context missing from the schema properties.
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 uses a specific verb ('Get') and resource ('high-level KPI overview') with clear scope ('for a project'). The 'high-level' qualifier adds meaningful scope but does not explicitly differentiate from siblings like `get_analytics_components_kpi` or `get_analytics_kpi_aggregation`.
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 versus the numerous sibling analytics tools (e.g., `get_analytics_components_kpi`, `get_analytics_kpi_aggregation`). No prerequisites or exclusions are mentioned despite the crowded tool namespace.
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 the full burden of disclosure but only states 'Get'. It fails to clarify if this is a cached operation, if it returns large datasets requiring pagination, or any authentication requirements specific to listing apps.
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, efficient sentence with no wasted words. However, it lacks front-loaded context that could help distinguish this from sibling operations given the tool-rich domain.
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?
Incomplete for a complex domain with many siblings (instances, components, analytics). Without an output schema or annotations, the description should explain what constitutes a 'controls app', its relationship to instances, or the return format, but provides none of this context.
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 input schema contains zero parameters, establishing a baseline score per the rubric. The description appropriately implies no filtering or identification parameters are needed.
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?
Clearly states the action (Get) and resource (controls apps) with scope (all available). However, it does not explicitly differentiate from the sibling tool `get_controls_app` (singular), which likely retrieves a specific app by ID.
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?
Provides no guidance on when to use this tool versus alternatives like `get_controls_instance` or `get_controls_app`, nor does it mention prerequisites or filtering capabilities.
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 the full burden of behavioral disclosure. It states 'Get' suggesting read-only behavior, but fails to disclose auth requirements, rate limits, error conditions (e.g., invalid project_id), or the structure/format of returned data. The term 'controls instances' is also not defined.
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 appropriately brief with no redundant text. The Args section format is clear and scannable. However, it could benefit from a single sentence explaining that results are paginated before jumping to the argument list.
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 zero annotations, no output schema, and minimal parameter documentation, the description is inadequate. It provides no information about return value structure, entity relationships, or behavioral side effects, leaving significant gaps for an AI agent attempting to invoke this tool correctly.
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?
Despite 0% schema description coverage (only titles present), the Args section successfully documents all three parameters with basic semantic meaning: project_id is 'numeric', page is 'Page number', and per_page clarifies 'Items per page'. This compensates for the schema deficiency, though it lacks detail on pagination mechanics (e.g., null behavior).
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 ('Get') and resource ('controls instances') with scope ('in a project'), making the basic purpose clear. However, it fails to distinguish from the sibling tool 'get_controls_instance' (singular), which likely retrieves a specific instance rather than a list.
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 list endpoint versus the singular 'get_controls_instance', nor does it explain pagination strategies (e.g., when to paginate vs requesting all items). The Args section documents parameters but offers no usage context.
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, placing full burden on the description. While 'Get' implies read-only safety, the description fails to disclose whether this calculates data in real-time or retrieves cached reports, what constitutes 'energy efficiency' in this domain, valid values for units_system, or error conditions for invalid date ranges.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The Python-docstring style with an Args block is appropriate given the schema's lack of descriptions, though it creates a hybrid narrative/reference format. The first sentence establishes purpose quickly, and the Args section is necessary given context, avoiding verbosity while ensuring all 4 parameters are documented.
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?
Given zero schema coverage and four parameters, the description achieves minimum viability by documenting all inputs. However, it lacks domain context (what the energy efficiency analysis calculates) and omits guidance on the output format despite having no output schema. Just adequate for the complexity level.
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?
With 0% schema description coverage, the Args block provides crucial semantic meaning: project_id is clarified as 'numeric ID', start/end specify 'ISO 8601 format' (critical for string parameters), and units_system is identified as a unit system. This effectively compensates for the schema's lack of descriptions.
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 clear verb ('Get') and resource ('energy efficiency analysis data') scoped to 'a project'. It distinguishes from siblings like get_project (general metadata) and get_analytics_instance_result (computational results) by focusing on energy efficiency specifically.
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 provided on when to use this tool versus alternatives like get_operational_optimization or get_technical_monitoring. No prerequisites or conditions mentioned despite the date range parameters implying temporal analysis requirements.
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 the full burden of behavioral disclosure but fails to mention idempotency, side effects, error conditions, or the structure of the return value despite confirmation that an output schema exists. It provides no context regarding whether adding a component triggers cascading operations, requires specific permissions, or validates against existing definitions.
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 appropriately brief with the primary action statement front-loaded, followed by a structured Args section that documents parameters efficiently without excessive verbosity. The two-line structure minimizes waste while conveying essential invocation context, though the docstring-style formatting is slightly informal.
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?
Given the simple two-parameter schema and existence of an output schema, the description adequately covers parameter identification through the Args block but remains incomplete regarding behavioral prerequisites, side effects, and mutation consequences necessary for robust agent decision-making.
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?
Despite 0% schema description coverage (only titles provided), the Args section provides crucial semantic clarification that 'component_id' refers specifically to a 'component definition ID' rather than an instance identifier, and confirms 'project_id' is numeric. This successfully compensates for the schema's generic titles by clarifying that the component parameter references a predefined definition rather than an arbitrary value.
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 the specific action 'Add' and target resource 'a component to a project,' clearly distinguishing it from sibling tools like 'delete_project_component' and 'get_project_components' through verb choice. However, it lacks domain-specific clarity regarding what constitutes a 'component' in this system (e.g., whether it's a device, module, or configuration element) given the presence of related component definition and attribute tools among siblings.
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 explicit guidance on when to use this tool versus alternatives, prerequisites such as component definition creation or project existence, or conditions where the operation might fail. There is no indication of whether the component definition must already exist in the system or how this relates to the 'get_components' or 'get_component_attribute_definitions' workflows suggested by sibling tools.
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 burden for behavioral disclosure. It states this is a creation operation but doesn't mention permissions required, whether it's idempotent, what happens on duplicate names, or what the output contains. For a mutation tool with zero annotation coverage, this is insufficient.
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 well-structured with a clear purpose statement followed by parameter explanations. It's appropriately sized with no redundant information. The only improvement would be integrating the parameter information more seamlessly rather than using a separate 'Args:' section.
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?
Given that there's an output schema (which handles return values), no annotations, and the description covers parameter semantics well, this is adequate for a creation tool. However, it lacks important behavioral context like permissions, idempotency, or error conditions that would be helpful for an AI agent.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear semantic meaning for all three parameters ('project_id: The project's numeric ID', 'name: Logbook name', 'description: Logbook description'), which adds significant value beyond the bare schema. The only minor gap is not explaining that description is optional.
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 action ('Create a new logbook') and resource ('in a project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_logbook_entry' or 'get_logbooks', which would be needed for a perfect score.
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 alternatives. With siblings like 'create_logbook_entry' (for entries within logbooks) and 'get_logbooks' (for reading), there's clear potential for confusion that the description doesn't address.
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 the full burden of behavioral disclosure. While 'Create' implies a write/mutation operation, the description doesn't address critical behavioral aspects: what permissions are required, whether the operation is idempotent, what happens on failure, what the response contains, or any rate limits. For a mutation tool with zero annotation coverage, this leaves significant gaps.
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 efficiently structured with a clear purpose statement followed by parameter documentation. Every sentence serves a purpose, though the parameter descriptions could be slightly more detailed given the 0% schema coverage. The formatting with 'Args:' section is helpful for readability.
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?
Given that this is a mutation tool with no annotations, 3 parameters (2 required), and an output schema exists, the description does an adequate but incomplete job. It covers the basic purpose and parameters but lacks behavioral context, usage guidance, and doesn't leverage the existence of an output schema to explain what the tool returns. For a create operation, more context about the created resource would be helpful.
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 description explicitly lists and briefly describes all three parameters (project_id, title, description), adding meaningful context beyond the schema. Since schema description coverage is 0%, this parameter documentation in the description is essential and well-executed, though it could provide more detail about format constraints or examples.
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 action ('Create a new task') and the target resource ('in a project'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling tools like 'create_project' or 'assign_task' beyond the obvious resource difference, which prevents a perfect score.
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 alternatives. There's no mention of prerequisites (e.g., needing an existing project), comparison to similar tools like 'create_project' or 'update_task', or any context about when this operation is appropriate versus when other task-related tools might be better suited.
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 the full disclosure burden but fails to explain activation behavior, side effects (e.g., immediate alert evaluation), or mutation characteristics. It does not clarify what happens when multiple thresholds are defined, if null thresholds disable that severity level, or whether alerts are active immediately upon creation.
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 structure is efficient with a clear single-sentence purpose followed by a structured parameter list. Each sentence earns its place with no redundant prose. The Args format is appropriate given the complete lack of schema descriptions, though grouping related parameters (thresholds vs notifications) would improve scannability.
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?
While the description covers all 9 parameters and the tool has an output schema (reducing the need for return value description), it lacks important contextual details for a monitoring/alerting tool: threshold precedence logic, notification delivery guarantees, and the interaction between optional null defaults and alert behavior. Adequate but incomplete given the domain complexity.
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?
Given 0% schema description coverage, the Args block provides crucial semantic context: 'datapoint to monitor' explains the resource relationship, severity levels (info/warn/crit) add domain meaning, and 'evaluation period in seconds' clarifies the temporal aspect. Minor deduction for not explaining null-default behavior or whether at least one notification channel is required.
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 specific verb (Create) and resource (threshold-based alert) with the 'new' qualifier distinguishing it from the sibling update_threshold_alert. However, it does not explicitly differentiate from other alert management tools like delete_alert or enable_alert, nor does it reference when to prefer this over updating existing alerts.
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 alternatives (e.g., updating existing alerts with update_threshold_alert), nor does it mention prerequisites like project existence or datapoint availability. There are no warnings about required vs optional notification channels.
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 the full burden but merely restates the destructive nature implied by the tool name. It omits critical behavioral details: whether deletion is permanent, if it affects historical data, cascade effects on associated systems, or what the output schema 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?
Extremely concise at three lines. The Args format is functional but reads like API documentation rather than a natural language description; front-loading the behavioral implications before the parameter list would improve structure.
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?
Adequate for a simple two-parameter deletion tool given that an output schema exists separately. However, it lacks context on whether setpoint IDs are globally unique or project-scoped, and whether the deletion is synchronous or queued.
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?
Given 0% schema description coverage, the Args section provides essential documentation for both parameters. However, the descriptions are minimal ('The project's numeric ID', 'The setpoint ID') and could clarify the hierarchical relationship (e.g., that setpoint_id exists within the scope of project_id).
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?
States specific verb (Delete) and resource (setpoint), making the core action unambiguous. However, it fails to distinguish from sibling `write_setpoint` (which may update values) or clarify if this permanently removes the setpoint versus disabling it.
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?
Provides no guidance on when to use this versus alternatives like `write_setpoint`, or prerequisites such as checking the setpoint status first. No mention of permissions or if the setpoint must be inactive before deletion.
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 full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't address important behavioral aspects like authentication requirements, rate limits, error conditions, or what constitutes 'details' (though output schema exists). For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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 appropriately concise with a clear purpose statement followed by parameter explanations. The two-sentence structure is efficient with zero wasted words. However, the formatting with 'Args:' on a separate line is slightly less optimal than integrating parameter information more seamlessly into the description flow.
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?
Given the tool's moderate complexity (2 required parameters), zero annotation coverage, but presence of an output schema, the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context and usage guidance. The output schema existence means return values documentation isn't needed, but other gaps remain for a tool that likely requires specific permissions and has operational constraints.
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?
With 0% schema description coverage, the description adds crucial parameter information that the schema lacks. The Args section clearly explains what 'instance_id' and 'project_id' represent, providing semantic meaning beyond the schema's bare type declarations. This effectively compensates for the schema's lack of descriptions, though it doesn't provide format examples or constraints.
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 purpose with a specific verb ('Get') and resource ('analytics instance's details'), making it immediately understandable. However, it doesn't distinguish this tool from sibling tools like 'get_analytics_instances' (plural) or 'get_analytics_instance_status', leaving some ambiguity about when to use this specific retrieval tool versus others.
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 alternatives. With sibling tools like 'get_analytics_instances' (list all instances) and 'get_analytics_instance_status' (get status specifically), the agent receives no help in choosing between these similar retrieval operations. The description merely states what the tool does without contextual usage information.
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. Beyond stating it retrieves details, it does not indicate if the operation is safe, idempotent, what specific data is returned, or error behaviors (though the existence of an output schema covers return format).
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?
Efficiently structured with the purpose in the first sentence followed by parameter documentation. No filler content, though the 'Args' block formatting is slightly informal for an MCP description.
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?
Adequate for a single-parameter read operation with an output schema present. However, given the complexity of the sibling tool ecosystem (multiple user-related getters), it lacks necessary disambiguation to ensure correct tool selection.
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?
With 0% schema description coverage, the description must compensate. The 'Args' block provides essential semantic mapping for 'user_id' ('The user's numeric ID'), explaining what the parameter represents, which is absent from the schema.
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?
States a specific verb ('Get') and resource ('details of a user'), with clear scope ('within the company'). However, it does not differentiate from the similarly-named sibling tool 'get_user', which may confuse agent selection.
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?
Provides no guidance on when to use this tool versus alternatives like 'get_user' or 'get_realm_users'. Does not mention prerequisites or error conditions.
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 provided, so description carries full disclosure burden. Beyond stating 'Get', offers no details on read-only safety, error handling (invalid project_id), rate limits, data freshness, or return format. Assumes standard read behavior without confirming.
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?
Extremely compact (2 sentences). Purpose statement is front-loaded, followed by Args section. No wasted words, though brevity is excessive given lack of annotations and output schema—slightly more context would be justified without hurting 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?
With only 1 parameter and no output schema, the description covers minimum viable ground: what it does and the parameter meaning. Missing: nature of compliance data returned, relationship to sibling monitoring/efficiency tools, and error scenarios. Adequate but minimal.
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?
Schema has 0% description coverage (no 'description' fields in properties). The Args section documents project_id as 'The project's numeric ID', providing essential semantics missing from schema. Compensates for schema gap but lacks constraint details or value examples.
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?
States specific verb (Get) and resource (compliance data for a project). Distinguishes from sibling 'get_project' and other getters by specifying 'compliance' domain, though could clarify what type of compliance (regulatory, technical, etc.) for full distinction.
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 versus alternatives like get_project or get_technical_monitoring. No mention of prerequisites (e.g., project existence checks) or conditions where this should be preferred over other project data retrieval tools.
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 burden for behavioral disclosure. It only implies read-only safety via 'Get' but doesn't disclose error behaviors (e.g., what happens if project_id or cip_id is invalid), rate limits, or performance characteristics.
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?
Extremely terse at three lines. The Args block is clear and efficient, though slightly formal. No redundant or wasted text, though the formatting could integrate better with the single sentence description.
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?
Given the output schema exists, it doesn't need to describe return values. The two parameters are documented in the description text. However, given the rich set of sibling tools (get_component_pins, get_component_attribute_definitions), the description should clarify what constitutes an 'attribute' versus other component data.
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?
With 0% schema description coverage, the description compensates adequately by documenting both parameters: clarifying project_id as 'numeric ID' and defining cip_id as 'component-in-project ID' (expanding the acronym).
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?
States specific action ('Get') and resource ('attributes of a component') with clear scope ('in a project'). However, it doesn't differentiate well from siblings like get_project_component (the component itself) vs get_component_attribute_definitions (the schema for attributes).
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 versus related tools like get_component_pins, get_component_results, or get_project_component. No mention of prerequisites or error conditions.
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 burden for behavioral disclosure. While 'Get' implies a read-only operation, it doesn't specify whether this requires authentication, returns paginated results, has rate limits, or what format the labels come in. The description is too minimal for a tool that likely interacts with a labeling system.
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 efficiently structured with a clear purpose statement followed by parameter documentation. Every sentence serves a purpose, though the parameter explanations could be slightly more detailed given the lack of schema descriptions.
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 read operation with 2 parameters and an output schema (which handles return values), the description is minimally adequate. However, with no annotations and 0% schema description coverage, it should provide more behavioral context about authentication needs, error conditions, or response structure to be truly complete.
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 description explicitly documents both parameters (project_id and datapoint_id) with brief explanations, which is valuable since the schema has 0% description coverage. While it doesn't elaborate on parameter formats or constraints, it provides essential semantic context that the schema lacks entirely.
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 action ('Get all labels') and resource ('assigned to a datapoint'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar sibling tools like 'get_project_labels' or 'get_company_labels', which prevents a perfect score.
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 alternatives. There's no mention of prerequisites, related tools, or scenarios where this specific label retrieval is appropriate versus other label-related tools in the sibling list.
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 the full burden of behavioral disclosure. It states the tool 'Get timeseries data,' implying a read-only operation, but doesn't clarify aspects like authentication requirements, rate limits, error handling, or data format. For a tool with 10 parameters, this lack of context is a significant gap in transparency.
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 well-structured and front-loaded: the first sentence states the purpose clearly, followed by a bulleted list of parameters. It avoids unnecessary fluff and each sentence serves a purpose. However, the parameter explanations could be more concise (e.g., combining similar parameters), and it lacks a concluding summary.
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?
Given the tool's complexity (10 parameters, no annotations, but has an output schema), the description is moderately complete. It covers the purpose and parameters but misses behavioral context and usage guidelines. The output schema likely handles return values, so that gap is acceptable. Overall, it's adequate but has clear room for improvement in guiding the agent.
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 description includes an 'Args:' section that lists all 10 parameters with brief explanations (e.g., 'Start time in ISO 8601 format,' 'Resample interval'). Since schema description coverage is 0%, this adds substantial value beyond the schema, which only provides titles and types. However, it doesn't detail default behaviors or constraints (e.g., valid values for 'interpolation'), keeping it from a perfect score.
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 purpose: 'Get timeseries data for a single datapoint.' It specifies the verb ('Get') and resource ('timeseries data for a single datapoint'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_project_timeseries' or 'get_datapoint', which might retrieve different scopes of data.
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 alternatives. It lacks context about prerequisites (e.g., needing a valid project_id and datapoint_id), and doesn't mention sibling tools like 'get_project_timeseries' for broader queries or 'get_datapoint' for non-timeseries data. This omission could lead to confusion in tool selection.
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 zero annotations provided, the description carries the full disclosure burden but fails to specify behavioral details such as sorting order (chronological?), pagination defaults (does null return all or first page?), or error conditions (e.g., invalid project_id).
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 compact with no wasted prose. The Args block is necessary given the schema lacks descriptions, though the structure is slightly utilitarian rather than narrative.
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?
Minimal but adequate given an output schema exists. The description covers the basic retrieval operation and parameter purposes, but omits pagination logic and sibling relationships that would help an agent understand the full comment lifecycle (add/get/delete).
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?
With 0% schema description coverage, the Args block compensates by documenting all three parameters. While 'Page number' and 'Items per page' are somewhat tautological, 'The project's numeric ID' clarifies the expected type and reference for project_id.
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 clear verb ('Get') and resource ('comments for a project'), identifying the tool's function. However, it does not explicitly distinguish from the sibling tool 'get_task_comment' to clarify this retrieves project-level rather than task-level comments.
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 usage guidance is provided. The description lacks information on when to use pagination (page/per_page) versus retrieving all comments, and does not indicate maximum values for per_page or behavior when parameters are null (default).
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. It states the tool 'Get[s] a specific component,' implying a read-only operation, but does not specify permissions needed, rate limits, error handling, or what 'Get' entails (e.g., returns metadata, full details). For a tool with no annotations, this is a significant gap in transparency.
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 front-loaded with the purpose in the first sentence, followed by parameter explanations. It is appropriately sized with no redundant information, though the parameter section could be more integrated. Every sentence earns its place, but the structure is slightly fragmented.
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?
Given that an output schema exists, the description does not need to explain return values. However, with no annotations, 0% schema description coverage, and two parameters, the description provides basic purpose and parameter semantics but lacks behavioral context and usage guidelines. It is minimally adequate but has clear gaps for a read operation tool.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaning by explaining 'project_id: The project's numeric ID' and 'cip_id: The component-in-project ID,' clarifying what these IDs represent beyond the schema's basic types. However, it does not provide format examples or constraints, leaving some ambiguity.
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 purpose: 'Get a specific component in a project.' It uses a specific verb ('Get') and resource ('component in a project'), but does not differentiate from sibling tools like 'get_project_components' (plural) or 'get_components' (general). This makes it clear but not fully distinguished from 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 is provided on when to use this tool versus alternatives such as 'get_project_components' or 'get_components'. The description only states what it does, without context on prerequisites, exclusions, or comparison to siblings. This leaves the agent to infer usage from the tool name alone.
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?
Annotations are absent, yet description provides no behavioral context beyond argument listing. Does not indicate this is a safe read-only operation (important given destructive siblings exist), disclose pagination limits, or explain error conditions.
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?
Docstring-style Args block is efficiently structured. First sentence establishes purpose; subsequent lines map parameters. No redundant prose, though slightly mechanical.
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?
Covers required parameter (project_id) and pagination options. Output schema is present so return values need not be described, but lacks usage context and behavioral safety disclosure needed for a tool among many project-related mutations.
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?
With 0% schema coverage, description compensates by documenting all 3 parameters in the Args block. Justification for integer/null union on pagination params would strengthen this, but basic semantics are covered.
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?
States specific action (Get) and resource (components) with scope (in a project). Distinguishes from global `get_components` via project scoping, but does not clarify difference from singular `get_project_component`.
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 versus `get_project_component` or `get_components`. No explanation of pagination strategy or default behavior when page/per_page are omitted.
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 full burden. It states this is a 'Get' operation, implying read-only behavior, but doesn't disclose any behavioral traits like authentication requirements, rate limits, error conditions, or what format the permissions are returned in. For a tool with no annotation coverage, this is a significant gap.
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 appropriately sized with two sentences: one stating the purpose and another explaining the parameter. It's front-loaded with the core functionality. There's minimal waste, though the 'Args:' section could be integrated more smoothly.
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?
Given the tool has an output schema (which handles return values), no annotations, and low complexity, the description is minimally adequate. However, it lacks context about the system's permission model or how this tool fits with siblings, leaving gaps for an AI agent to infer usage correctly.
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 description adds the parameter 'project_id' with clarification that it's 'The project's numeric ID', which provides useful semantic context beyond the schema's basic type (integer). With 0% schema description coverage and only 1 parameter, this compensates adequately, though it could mention format constraints or examples.
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 verb ('Get') and resource ('permissions configured for a project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_company_permissions' or 'get_user_permissions', which would be needed for a perfect score.
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 alternatives like 'get_company_permissions' or 'get_user_permissions'. It also doesn't mention prerequisites such as required permissions or context about what 'permissions' entail in this system.
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 states this is a 'Get' operation, implying read-only behavior, but doesn't disclose other traits like authentication needs, rate limits, error conditions, or what the output contains (though an output schema exists). For a tool with no annotation coverage, this is a significant gap in 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, with the core purpose stated first followed by parameter explanations. Each sentence adds value, though the parameter section could be slightly more integrated into the main text for better flow.
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?
Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is adequate but incomplete. It covers the purpose and parameters well, but lacks usage guidelines and behavioral context. The output schema mitigates the need to explain return values, but overall, it's a minimal viable description with clear gaps.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics for all three parameters: 'project_id' is explained as 'The project's numeric ID', 'key' as 'Filter by tag key', and 'keys_only' as 'If true, return only tag keys without values'. This effectively documents parameter purposes beyond the bare schema, though it lacks format or constraint details.
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 verb ('Get') and resource ('all datapoint tags in a project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_project_labels' or 'get_project_datapoints', which might also retrieve project metadata, so it misses full sibling distinction.
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 alternatives. It doesn't mention prerequisites, such as needing an existing project, or compare it to similar tools like 'get_project_labels' or 'add_project_tag' from the sibling list, leaving usage context unclear.
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 full burden. 'Update company details' implies a mutation operation, but the description doesn't disclose behavioral traits like required permissions, whether changes are reversible, what happens to unspecified fields, or any rate limits. It mentions parameters but not the tool's overall behavior or effects.
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 appropriately sized and front-loaded: the first line states the purpose clearly, followed by parameter explanations. There's no wasted text. However, the structure with 'Args:' is slightly redundant since parameters are documented in the schema, though it adds clarity in this case.
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?
Given the tool's complexity (mutation with 2 parameters), no annotations, and an output schema present (which reduces need to describe returns), the description is minimally adequate. It covers purpose and parameters but lacks behavioral context, usage guidelines, and details on optionality. It meets baseline completeness but has clear gaps for a mutation tool.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics by explaining that 'name' is the 'New company name' and 'description' is the 'New company description', clarifying these are update values rather than identifiers. However, it doesn't address that both parameters are optional (default: null) or provide format constraints.
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 verb ('Update') and resource ('company details'), making the purpose immediately understandable. It distinguishes itself from siblings like 'update_project' or 'update_user' by specifying 'company' as the target resource. However, it doesn't specify what aspects of 'company details' are updated beyond the parameters mentioned.
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 alternatives. There's no mention of prerequisites (e.g., needing company ID or permissions), when not to use it, or how it differs from similar tools like 'update_project' or 'update_user'. The agent must infer usage from context alone.
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. While 'Delete' implies destruction, there is no disclosure about whether this is permanent, if it requires confirmation, affects active ai_chat sessions, or specific permissions needed given the destructive nature.
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 core action is front-loaded in the first sentence. The 'Args:' section is somewhat unconventional for MCP (typically belonging in schema descriptions) but is efficient. No extraneous information is included.
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 single-parameter destructive operation with an output schema present, the description is minimally adequate but lacks safety context. It does not address irreversibility, cascading effects, or the relationship to ongoing conversations that would help an agent invoke this safely.
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?
With 0% schema description coverage, the description minimally compensates by stating thread_id is 'The thread identifier.' This is tautological but provides the only semantic layer beyond the schema. It does not explain format constraints, examples, or how to obtain valid thread IDs.
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 verb ('Delete') and resource ('AI conversation thread'), clearly distinguishing it from sibling tools like ai_chat (interact), ai_get_thread (retrieve), and ai_get_threads (list).
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, prerequisites (e.g., whether the thread must be inactive), or warnings about irreversibility.
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 the full burden of behavioral disclosure. It indicates a destructive action ('Delete') and a confirmation requirement, but lacks details on permissions needed, whether deletion is reversible, what happens to associated data, or rate limits. This is insufficient for a high-stakes mutation tool.
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 front-loaded with the core action, followed by a brief explanation of the confirmation requirement and parameter details. Every sentence earns its place with no wasted words, making it highly efficient.
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?
Given that this is a destructive tool with no annotations, 0% schema description coverage, but an output schema exists, the description is moderately complete. It covers the basic action and parameters but lacks critical behavioral details like error handling or side effects, which are essential for safe use.
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?
Schema description coverage is 0%, so the description must compensate. It explains both parameters: 'project_id' as 'The project's numeric ID' and 'project_name' as 'The project name (for confirmation),' adding clear meaning beyond the schema's basic types. However, it doesn't detail format constraints or examples.
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 verb ('Delete') and resource ('a project'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling deletion tools like 'delete_project_comment' or 'delete_project_component', which would be needed for a perfect score.
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 mentions 'Requires confirmation via the project name,' which provides some usage context but doesn't specify when to use this tool versus alternatives like 'delete_project_component' or 'delete_project_timeseries.' No explicit guidance on prerequisites or exclusions is given.
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 the full burden of behavioral disclosure. It states the action is 'Delete', implying a destructive mutation, but lacks critical details: it doesn't specify if deletion is permanent or reversible, what permissions are required, if there are rate limits, or what happens to associated data. This leaves significant gaps for safe agent operation.
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 highly concise and well-structured: a clear purpose statement followed by a bulleted list of parameters with essential details. Every sentence earns its place, with no redundant or verbose language, making it easy to parse quickly.
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?
Given the tool's complexity (destructive operation with 4 parameters, no annotations, but with an output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks behavioral context (e.g., safety, permissions) and doesn't explain when to use it versus siblings. The output schema existence means return values needn't be described, but overall completeness is limited.
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 description includes an 'Args' section that lists all four parameters with brief explanations, adding meaningful context beyond the schema (which has 0% description coverage). It clarifies that 'project_id' is numeric, 'datapoint_id' is an identifier, and 'start'/'end' use ISO 8601 format, though it doesn't detail default behaviors (e.g., null values meaning 'all time').
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 action ('Delete') and target resource ('timeseries data for a datapoint'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'delete_datapoint' or 'delete_project', which might handle broader deletions, leaving some ambiguity about 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 provided on when to use this tool versus alternatives. For example, it doesn't mention if this is for cleaning up specific time ranges versus deleting all data, or how it relates to siblings like 'delete_datapoint' (which might remove the datapoint entirely) or 'write_project_timeseries' (which could overwrite data).
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 full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, its permissions, rate limits, or response format (though output schema exists). For a tool with zero annotation coverage, this is inadequate.
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, efficient sentence with no wasted words, front-loading the core purpose. It's appropriately sized for a simple tool with no parameters.
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?
Given the tool's simplicity (0 parameters, output schema provided), the description is minimally adequate but lacks context for usage among siblings. With no annotations, it should ideally mention it's a read operation or list retrieval, but the output schema mitigates some gaps.
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 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't add parameter semantics, but with no parameters, a baseline of 4 is appropriate as no compensation is needed.
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 action ('Get') and resource ('all available analysis functions'), making the purpose evident. However, it doesn't differentiate from sibling tools like 'get_analytics_function' (singular) or 'get_analytics_components_kpi', leaving room for ambiguity about 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 provided on when to use this tool versus alternatives. With siblings like 'get_analytics_function' (likely for a specific function) and 'get_analytics_components_kpi' (likely for KPI data), the description lacks context for selection, offering only a basic statement without exclusions or prerequisites.
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 provided, so description carries full burden of behavioral disclosure. Fails to indicate whether this is read-only (though implied), what scope 'all labels' covers (global vs. user-accessible), or whether results are paginated. Context signals indicate output schema exists, but description doesn't hint at return structure.
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?
Extremely concise single sentence with no wasted words. Front-loaded with action verb. Appropriate length for a parameterless getter tool.
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?
Adequate for low-complexity tool (no params, output schema exists), but minimal. Given the rich label ecosystem visible in siblings (get_label_definitions, get_label_systems), description should clarify whether this returns label assignments on the company entity or available label definitions within the company scope.
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?
Input schema has zero parameters with 100% coverage. Per scoring rules, zero parameters establishes a baseline of 4. Description appropriately implies no filtering is possible by stating 'all labels'.
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?
States specific verb ('Get') and resource ('labels assigned to the company'). Distinguishes from sibling tools like get_project_labels and get_datapoint_labels by scoping to 'company' level. However, lacks clarity on what 'labels' represent (metadata tags vs. classification labels) and whether this returns assignments or definitions.
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?
Provides no guidance on when to use this tool versus siblings like get_label_definitions (which likely returns available label types) or get_project_labels. Does not mention that no parameters are required, which contrasts with most sibling getter tools that require IDs.
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 the full burden of behavioral disclosure. It states it's a read operation ('Get'), implying non-destructive behavior, but doesn't cover aspects like authentication requirements, rate limits, error conditions, or what the output contains. This leaves significant gaps for a tool that likely returns sensitive permission data.
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, efficient sentence that directly states the tool's purpose without any fluff or redundancy. It's front-loaded with the core action and resource, making it easy to parse quickly.
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?
Given the tool has no parameters and an output schema exists, the description adequately covers the basic purpose. However, with no annotations and a potentially complex output (permissions data), it lacks context on behavioral traits like security implications or data format. It's minimally viable but could benefit from more operational guidance.
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 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, and it correctly implies no inputs are required. A baseline of 4 is appropriate for zero-parameter tools when the description aligns with that.
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 action ('Get') and resource ('all project permissions granted to the company'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_project_permissions' or 'get_user_permissions', which would be needed for a perfect score.
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 alternatives like 'get_project_permissions' or 'get_user_permissions' from the sibling list. There's no mention of prerequisites, context, or exclusions, leaving the agent with minimal usage direction.
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 states it 'gets' data, implying a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, or what 'all roles' entails (e.g., whether it includes system roles or only custom ones). This leaves significant gaps for an agent to understand how to use it effectively.
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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.
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?
Given the tool's simplicity (0 parameters, output schema exists), the description is minimally adequate. However, with no annotations and no output schema details in the description, it lacks context on what the return data looks like or any behavioral constraints, leaving room for improvement despite the low complexity.
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 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add parameter semantics, but that's acceptable here as there are no parameters to document, warranting a baseline score of 4.
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 verb 'Get' and resource 'all roles defined in the company', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_user_roles' or 'get_company_permissions', which could retrieve related but different data.
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 alternatives. It doesn't mention prerequisites, context (e.g., admin vs. regular user access), or compare it to similar tools like 'get_user_roles' or 'get_company_permissions' in the sibling list.
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 full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't specify whether this returns all components at once or uses pagination, what format the definitions are in, or any authentication requirements. For a tool with zero annotation coverage, this leaves significant behavioral gaps.
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, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and gets straight to the point.
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?
Given the tool's simplicity (0 parameters, output schema exists) and lack of annotations, the description is adequate but minimal. While the output schema will document return values, the description doesn't provide context about what 'component definitions' encompass or how this differs from related sibling tools, leaving room for improvement.
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 0 parameters with 100% schema description coverage, so the schema already fully documents the absence of parameters. The description appropriately doesn't waste space discussing nonexistent parameters, earning a baseline score above minimum viable.
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 action ('Get') and resource ('all available component definitions'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_component_attribute_definitions' or 'get_component_pin_definitions' that also retrieve component-related information, preventing a perfect score.
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 alternatives. With many sibling tools retrieving component-related data (e.g., get_component_attribute_definitions, get_component_pins), there's no indication of what makes this tool distinct or when it should be preferred over others.
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 full burden. It states a read operation ('Get'), implying it's likely safe, but doesn't disclose behavioral traits like authentication needs, rate limits, pagination, or what 'all' entails (e.g., scope, format). This leaves significant gaps for an agent to understand how to invoke it effectively.
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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded and wastes no space, making it easy for an agent to parse quickly.
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?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, with no annotations and many sibling tools, it lacks context on usage and behavior, which could hinder an agent's ability to select and invoke it correctly in complex scenarios.
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 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for this scenario is 4, as the description appropriately doesn't add redundant information, and the absence of parameters is clear from the schema.
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 action ('Get') and resource ('all label definitions available in aedifion'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'get_label_systems' or 'get_company_labels', which might retrieve related but different resources.
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 alternatives. With many sibling 'get_' tools (e.g., 'get_label_systems', 'get_company_labels'), there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.
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 full burden. It states 'Get' which implies a read-only operation, but doesn't disclose any behavioral traits like authentication requirements, rate limits, response format, or whether it returns all systems or requires filtering. For a tool with zero annotation coverage, this is insufficient.
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, efficient sentence with no wasted words. It's front-loaded with the core purpose and includes helpful examples. Every part of the sentence earns its place.
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?
Given the tool's simplicity (0 parameters, output schema exists), the description is minimally adequate. However, with no annotations and many sibling tools, it lacks context about when this tool fits into workflows. The output schema will handle return values, but behavioral aspects are underspecified.
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 0 parameters, and schema description coverage is 100% (empty schema). The description doesn't need to add parameter semantics, so a baseline of 4 is appropriate. It does mention examples of what might be returned ('e.g., SI, imperial'), which adds slight context about output.
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 verb 'Get' and the resource 'available label/unit systems', with specific examples like 'SI, imperial'. However, it doesn't explicitly distinguish this tool from potential siblings like 'get_label_definitions' or 'get_company_labels' that might exist in the list, though those appear to be different resources.
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 alternatives. It doesn't mention prerequisites, context, or any sibling tools that might be related (e.g., for creating or updating label systems). The agent must infer usage solely from the tool name and description.
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 burden for behavioral disclosure. It mentions pagination parameters but doesn't describe important behaviors like whether this is a read-only operation, what authentication is required, rate limits, error conditions, or the structure of returned user data. The mention of pagination is helpful but insufficient for a tool with no annotation coverage.
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 extremely concise and well-structured: a clear purpose statement followed by parameter explanations. Every sentence serves a purpose with zero wasted words, making it easy to parse quickly.
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?
Given that an output schema exists (which handles return values), the description covers the basic purpose and parameters adequately. However, for a tool with no annotations and 2 parameters, it should ideally include more behavioral context about authentication, rate limits, or error handling to be fully complete.
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?
With 0% schema description coverage and 2 parameters, the description provides clear semantic information about both parameters ('page: Page number' and 'per_page: Items per page'), explaining their purpose in pagination. This effectively compensates for the lack of schema descriptions, though it doesn't specify default values or constraints.
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 purpose with 'Get all users in the realm' - a specific verb ('Get') and resource ('users in the realm'). However, it doesn't differentiate from potential sibling tools like 'get_user' or 'get_company_user', which might retrieve individual users rather than all realm users.
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 about when to use this tool versus alternatives. The description doesn't mention prerequisites, appropriate contexts, or comparisons to similar tools like 'get_user' or 'get_company_user' from the sibling list.
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 the full burden of behavioral disclosure. It mentions retrieving details but doesn't specify what details are included, whether it's read-only, if authentication is required, or any rate limits. This leaves significant gaps for a tool that likely involves user data.
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, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse.
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?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description doesn't need to explain parameters or return values. However, with no annotations and a simple purpose, it could benefit from more behavioral context (e.g., authentication needs, data scope), but it's minimally adequate for a read operation.
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 0 parameters, and the schema description coverage is 100%, so no parameter information is needed. The description appropriately doesn't discuss parameters, aligning with the schema. A baseline of 4 is applied since it doesn't add unnecessary details.
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 verb ('Get') and resource ('currently logged-in user's details'), making the purpose specific and understandable. It doesn't explicitly distinguish from sibling tools like 'get_company_user' or 'get_realm_users', but those target different resources, so differentiation is somewhat inherent.
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 alternatives like 'get_company_user' or 'get_realm_users', nor does it mention any prerequisites or context for usage. It simply states what it does without indicating appropriate 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 are provided, so the description carries full burden. It states a read operation ('Get'), which suggests non-destructive behavior, but doesn't disclose any behavioral traits such as authentication requirements, rate limits, error conditions, or what the output contains. This leaves significant gaps for an agent to understand how to use it effectively.
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, clear sentence with no wasted words. It's front-loaded with the essential purpose, making it highly efficient and easy to parse.
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?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is minimally adequate. However, with no annotations and a read operation that might involve user context or permissions, the description could benefit from more behavioral context to be fully complete for an agent.
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 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The description doesn't add parameter semantics, but that's unnecessary here. A baseline of 4 is appropriate as the schema fully covers the absence of parameters.
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 action ('Get') and the resource ('the logged-in user's project permissions'), making the purpose unambiguous. It doesn't explicitly differentiate from sibling tools like 'get_company_permissions' or 'get_project_permissions', but the specificity about 'user' and 'project' provides implicit distinction.
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 like 'get_company_permissions' or 'get_project_permissions'. The description implies it's for retrieving permissions specific to the logged-in user and projects, but lacks explicit context about prerequisites or comparison to siblings.
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. It mentions the action ('grant or revoke') but does not specify permissions required, side effects (e.g., impact on AI features), rate limits, or response behavior. The output schema exists but is not described, leaving gaps in understanding the tool's effects.
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 front-loaded with the purpose in the first sentence, followed by a concise 'Args' section. Every sentence earns its place with no wasted words, making it easy to scan and understand quickly.
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?
Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is minimally adequate. It covers the purpose and parameters but misses behavioral context and usage guidelines. The output schema helps, but the description does not reference it, leaving completeness gaps for a mutation tool.
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?
Schema description coverage is 0%, but the description compensates by explaining both parameters: 'project_id: The project's numeric ID' and 'consent: True to grant, False to revoke.' This adds clear meaning beyond the schema's basic types. However, it lacks details like ID format or consent implications, keeping it from a perfect score.
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 purpose: 'Grant or revoke consent for the AI Assistant on a project.' It specifies the verb ('grant or revoke'), resource ('consent for the AI Assistant'), and scope ('on a project'). However, it does not explicitly differentiate from sibling tools like 'ai_chat' or 'ai_get_threads', which are related to AI interactions but serve different purposes.
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 alternatives. It lacks context such as prerequisites (e.g., needing project access), exclusions (e.g., not for general AI settings), or comparisons to siblings like 'ai_chat' or 'create_user'. Without this, users must infer usage from the purpose alone.
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. While 'Set' implies a write/mutation operation, it doesn't disclose critical behavioral traits like required permissions, whether this overwrites existing renamings, error conditions, or what the output contains. The description is too minimal for a mutation tool with zero annotation coverage.
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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence adds value without redundancy, and it's appropriately front-loaded with the main functionality.
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?
Given that this is a mutation tool with no annotations, 0% schema description coverage, but with an output schema present, the description is moderately complete. It covers the basic purpose and parameter semantics adequately, but lacks behavioral context (like side effects or error handling) that would be crucial for safe usage. The output schema reduces the need to describe return values.
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?
Schema description coverage is 0%, so the description must compensate. It adds meaningful context for both parameters: 'project_id' is clarified as 'numeric ID', and 'renamings' is explained as a 'JSON string with renaming mappings' including the structure ('list of {dataPointID, alternateKey}'). This goes well beyond the bare schema, though it could specify JSON format details for a perfect score.
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 action ('Set alternate keys') and resource ('for datapoints in a project'), making the purpose specific and understandable. However, it doesn't explicitly differentiate this tool from similar-sounding siblings like 'update_datapoint' or 'get_datapoint_labels', which would be needed for a perfect score.
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 alternatives. With many sibling tools related to datapoints and projects (e.g., 'update_datapoint', 'get_datapoint_labels'), there's no indication of prerequisites, typical use cases, or when other tools might be more appropriate.
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 full burden. 'List all available API endpoints' implies a read-only operation but doesn't disclose whether this requires authentication, has rate limits, returns structured data, or provides metadata about endpoints. For a tool with zero annotation coverage, this is insufficient behavioral disclosure.
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, efficient sentence with zero waste. It's front-loaded with the core action ('List all available API endpoints') and contains no unnecessary words or redundant information.
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?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists, the description is reasonably complete for its purpose. However, with no annotations and many sibling tools, it could benefit from more context about when this discovery tool is most useful in the broader API workflow.
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 0 parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters since none exist. It correctly focuses on what the tool does rather than parameter details.
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 purpose with a specific verb ('List') and resource ('all available API endpoints'). It distinguishes itself from siblings by focusing on endpoint discovery rather than data manipulation. However, it doesn't explicitly differentiate from other 'get_' tools that retrieve specific resources.
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 alternatives. With many sibling tools (over 100), there's no indication whether this should be used for initial discovery, debugging, or understanding API capabilities. No prerequisites or exclusions 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 full burden for behavioral disclosure. It states it's a read operation ('Get'), but doesn't mention whether it requires authentication, has rate limits, returns paginated results, or what happens if the project doesn't exist. For a tool with no annotation coverage, this leaves significant behavioral gaps.
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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by a clear 'Args' section. There's no redundant information, and every sentence earns its place by adding value.
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?
Given the tool has an output schema (which handles return values), 1 parameter with 0% schema coverage (compensated by the description), and no annotations, the description is reasonably complete. It covers the purpose and parameter meaning, but lacks behavioral details like error handling or usage context, which would be beneficial for full completeness.
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 description includes an 'Args' section that explains 'project_id' as 'The project's numeric ID', adding meaningful context beyond the schema's basic type (integer) and title (Project Id). With 0% schema description coverage, this compensates well for the single parameter, though it could specify format constraints like positive integers only.
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 verb 'Get' and the resource 'all labels assigned to a project', making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_company_labels' or 'get_datapoint_labels', which reduces clarity about when this exact tool is appropriate versus 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?
The description provides no guidance on when to use this tool versus alternatives like 'get_company_labels' or 'get_datapoint_labels'. It also doesn't mention prerequisites, such as needing an existing project ID, or contextual constraints like permissions required to access project labels.
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 full burden of behavioral disclosure. It successfully explains processing behaviors like resampling (samplerate), interpolation, aggregation methods, and format options (short). However, it fails to disclose operational traits like read-only safety, rate limits, behavior when datapoints are missing, or data retention limits.
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 follows a logical docstring structure with the high-level purpose front-loaded, followed by an Args block. Given the necessity of documenting 11 parameters with 0% schema coverage, the length is appropriate. Each parameter entry is dense and necessary, though the format could be more narrative rather than docstring-style for MCP contexts.
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 complex tool with resampling/aggregation logic and an output schema present, the description adequately covers parameter semantics and processing options. However, it omits error handling patterns, relationships between entities (e.g., that datapoints must belong to the specified project_id), and pagination behavior for the 'max' parameter.
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?
Given 0% schema description coverage (only titles present), the Args block provides substantial compensation by documenting all 11 parameters with types, formats (e.g., 'ISO 8601', 'comma-separated'), and examples (e.g., '15min', 'linear'). It clarifies that datapoint_ids expects comma-separated hash keys, which the schema only types as 'string'. Minor gap: doesn't indicate required vs. optional parameters in the text.
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 action (Get), resource (time series data), and scope (one or more datapoints in a project). It implicitly distinguishes from the sibling `get_datapoint_timeseries` by emphasizing 'one or more' and 'in a project,' signaling batch/aggregate capability versus single-datapoint retrieval, though it could explicitly name the alternative for clarity.
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 alternatives like `get_datapoint_timeseries` (single vs. multiple datapoints) or `write_project_timeseries`. It lacks prerequisites, error conditions, or exclusion criteria, leaving the agent to infer usage context solely from parameter definitions.
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?
No annotations provided, so description carries full burden. Mentions BACnet priority range (1-16) which constrains behavior, but lacks disclosure of mutation semantics (overwrites existing?), idempotency, side effects on physical devices, or error handling. 'Write' implies mutation but safety characteristics unspecified.
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?
Standard Python docstring format with purpose front-loaded in first sentence followed by Args block. Appropriately sized given the need to document four parameters with no schema support. No unnecessary fluff, though 'The' prefixes in Args could be removed for tighter prose.
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?
Input parameters documented sufficiently given schema gaps, and presence of output schema (per context signals) excuses lack of return value description. However, for a BACnet control operation, lacks operational context (protocol handshaking, persistence guarantees, priority arbitration behavior) that would aid agent decision-making.
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?
With 0% schema description coverage, the Args section successfully documents all 4 parameters. Particularly adds value for 'priority' (BACnet protocol constraint 1-16) and 'project_id' (numeric constraint). 'Datapoint identifier' is redundant with schema title but acceptable given mandatory compensation for zero schema coverage.
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?
Clear verb 'Write' with specific resource 'setpoint value' and target 'datapoint'. Distinguishes from sibling operations like 'delete_setpoint' and 'get_setpoint_status' through the write/read/delete distinction, though could clarify what distinguishes a setpoint from other writable values (e.g., timeseries).
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?
Provides no guidance on when to use this versus 'write_project_timeseries' or other write operations. Does not explain when to use specific priority levels (1-16) or when null priority is appropriate. No prerequisites or error conditions 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?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a chat message sending operation but doesn't describe what happens after sending (e.g., does it return a response immediately? is it asynchronous?), authentication requirements, rate limits, or error conditions. The mention of thread management ('new' for new thread) adds some context but insufficient for a mutation tool.
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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence serves a purpose with zero wasted words. The two-sentence format with parameter details in a structured Args section is appropriately front-loaded and concise.
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?
Given that this is a mutation tool with no annotations but has an output schema, the description is moderately complete. It explains the core action and parameters adequately, and the output schema will handle return values. However, for an AI chat tool, more context about the assistant's capabilities, response format, or typical use cases would be helpful given the complexity of AI interactions.
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?
Schema description coverage is 0%, so the description must compensate. It provides clear documentation for both parameters: 'thread_id' with the special value 'new' for new threads, and 'message' as the content to send. This adds meaningful semantics beyond the bare schema, though it doesn't elaborate on thread persistence, message formatting, or length limits.
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 action ('Send a chat message') and target ('to the aedifion AI assistant'), making the purpose understandable. It distinguishes from siblings by focusing on AI chat functionality rather than project/task management or data operations. However, it doesn't specify what kind of responses to expect or the assistant's capabilities.
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 interacting with an AI assistant, but provides no explicit guidance on when to use this versus other tools. The parameter documentation mentions 'use 'new' for a new thread' which gives some implementation context, but doesn't address use cases, prerequisites, or alternatives among the many sibling tools.
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 full burden of behavioral disclosure. It identifies the read operation but omits details about caching, authentication requirements, or rate limiting. However, the existence of an output schema mitigates the need to describe return values, and the zero-parameter nature limits behavioral complexity.
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?
Single sentence with no redundant prose. The front-loaded structure immediately communicates intent without wasting tokens on obvious elaborations.
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?
Given the tool's low complexity (zero parameters), the presence of an output schema, and the self-evident nature of the operation, the description is sufficiently complete. It identifies what resource is accessed, which is adequate for this utility function.
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?
With zero parameters, the schema coverage is 100% by default. The description correctly implies no parameters are needed by focusing solely on the retrieval action, meeting the baseline expectation for arity-zero tools.
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 uses a specific verb ('Get') and identifies the exact resource ('aedifion API version'). While it does not explicitly contrast itself against sibling 'get_' tools, the target resource is unique enough to avoid confusion with other getters like get_project or get_user.
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 invoke this tool versus alternatives (e.g., 'ping' for connectivity checks), nor does it mention typical use cases like version compatibility checks.
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?
No annotations provided, so description carries full burden. Uses 'Get' implying read-only operation and mentions 'logged-in user' indicating session-scoped behavior, but lacks details on return structure, caching, rate limits, or error conditions (e.g., unauthenticated).
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?
Single 5-word sentence front-loaded with action verb. Zero redundancy or waste. Appropriate length for a zero-parameter getter.
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?
Adequate for a simple read operation with output schema present (per context signals). Doesn't explain return values but output schema exists. Could benefit from mentioning relationship to company roles or permissions systems given the sibling density.
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?
Input schema has 0 parameters (baseline 4 per rules). Description adds value by specifying 'logged-in user's roles', explaining why no user ID parameter appears (user inferred from authentication context), which helps agents understand the implicit parameterization.
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?
States specific verb (Get) and resource (logged-in user's roles). Distinguishes from get_company_roles (company-wide roles vs user-specific) and get_user_permissions (roles vs permissions), but could clarify what roles represent (e.g., admin versus viewer distinction) or explicitly contrast with siblings.
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 explicit guidance on when to use versus alternatives like get_company_roles or get_user_permissions. Missing prerequisites (e.g., requires active session) or typical use cases (e.g., 'use to check authorization before admin operations').
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?
No annotations provided, so description carries full burden. Adds valuable context by specifying 'current user' (indicating auth-scoped access) and 'including projects and users' (disclosing data richness/nesting). However, lacks details on caching, rate limits, or permissions required.
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?
Extremely concise at 9 words. Single sentence front-loaded with action verb ('Get'). No redundant words; every term adds specificity (current user, projects, users).
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?
Appropriate for a simple getter with 0 parameters and existing output schema. The description efficiently conveys the tool's scope without needing to document return values. Minor gap: could explicitly contrast with update_company or delete_company_user to clarify read-only nature.
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?
Zero parameters with 100% schema coverage (empty object). Per rubric, 0 params = baseline 4. Description appropriately omits parameter details since none exist.
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?
Clear verb (Get) + resource (company details) and scope (current user). Distinguishes from siblings like get_company_user (singular) and get_company_roles by mentioning it includes 'projects and users' (plural), suggesting a comprehensive company object return rather than specific aspects.
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?
Provides implied usage context—use this for retrieving the current user's company overview with nested projects and users. However, lacks explicit guidance on when to prefer this over specific getters like get_company_user, get_company_roles, or get_project, and doesn't mention prerequisites like authentication.
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?
No annotations provided, so description carries full burden. Mentions 'check availability' indicating read-only nature, but lacks disclosure of auth requirements, rate limits, timeout behavior, or what specific availability metrics are returned despite output schema existing.
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?
Single sentence, immediately front-loaded with action and purpose. No redundant phrases or wasted words. Appropriate length for zero-parameter tool.
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?
Sufficient for tool complexity: zero inputs, output schema exists to document return values. Description covers core intent. Lacks only operational details (timeout, retry behavior) that would make it fully comprehensive given no annotations.
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?
Zero parameters per schema, which per guidelines establishes baseline of 4. Description correctly implies no configuration needed for a ping operation, consistent with the empty properties object.
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?
Description uses specific verb 'Ping' with specific target 'aedifion API server' and specific outcome 'check availability'. Clear distinction from siblings like get_api_version or get_endpoints which retrieve data rather than test connectivity.
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?
Implies usage context (checking availability) but lacks explicit guidance on when to use versus other status-checking tools like get_api_version or get_analytics_status. No mention of prerequisites or typical calling patterns.
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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