AWS MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools are clearly distinct, targeting specific AWS services and operations (e.g., list_ec2_instances vs. get_instance_details). However, some overlap exists, such as list_recent_cloudtrail_events and list_cloudtrail_changes, which could cause confusion without careful reading of descriptions. Overall, the domain coverage is broad but well-organized.
Naming Consistency5/5
Tool names follow a highly consistent verb_noun pattern throughout, using snake_case uniformly. All tools start with verbs like 'get', 'list', 'check', or 'search', followed by specific nouns, making them predictable and easy to parse. No deviations or mixed conventions are present.
Tool Count2/5
With 58 tools, the count is excessive for a single server, making it overwhelming and likely to cause agent confusion. While AWS is a broad domain, this many tools suggests poor scoping; it would be more coherent if split into focused sub-servers (e.g., cost management, security, compute).
Completeness4/5
The tool set provides extensive coverage across AWS services, including monitoring, security, cost, and infrastructure, with many CRUD-like operations (e.g., list and get tools). Minor gaps exist, such as limited mutation tools (e.g., no create or delete operations), but agents can still perform comprehensive read-only analysis and diagnostics.
Average 3.1/5 across 58 of 58 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
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How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, requires permissions, has rate limits, returns paginated results, or includes metadata like ARNs. This is inadequate for a tool with potential 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?
The description is a single, efficient sentence with no wasted words, making it front-loaded and easy to parse. It directly states the tool's function without unnecessary elaboration.
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 no annotations, no output schema, and a simple parameter, the description is incomplete. It doesn't cover behavioral aspects like safety, permissions, or result format, which are crucial for an AI agent to use this tool effectively in an AWS context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'load_balancer_arn' documented as optional for filtering. The description adds no additional meaning beyond the schema, such as format examples or filtering implications, so it meets the baseline for high schema coverage.
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 'Lists all Target Groups' clearly states the verb ('Lists') and resource ('Target Groups'), providing a basic purpose. However, it lacks specificity about scope (e.g., AWS region, account) and doesn't distinguish from siblings like 'list_load_balancers' or 'get_target_health', making it vague in 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. It doesn't mention prerequisites, context (e.g., AWS environment), or compare to sibling tools like 'get_target_health' for health status or 'list_load_balancers' for related resources, leaving usage 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only list operation but doesn't disclose details like pagination, rate limits, authentication needs, or what 'available' means (e.g., region-specific, account-level). This is inadequate for a 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 a single, efficient sentence with no wasted words, making it easy to parse. However, it's front-loaded but could be more structured by including key details like scope or usage context to enhance clarity without sacrificing brevity.
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 simplicity (0 parameters, no output schema) and lack of annotations, the description is incomplete. It doesn't explain what Trusted Advisor checks are, the return format, or behavioral traits, leaving gaps that could hinder an agent's ability to use it effectively in context with many sibling tools.
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 no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 as it avoids redundancy while the schema fully covers the empty parameter set.
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 'Lists Trusted Advisor checks available' clearly states the verb ('Lists') and resource ('Trusted Advisor checks'), but it's vague about scope and doesn't differentiate from siblings. It doesn't specify whether this lists all checks, only enabled ones, or checks for specific services, which could help distinguish it from other list_* 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 (e.g., AWS Trusted Advisor access), context for usage, or how it relates to other AWS monitoring 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 checks for IP existence in WAF IP Sets, implying a read-only operation, but does not disclose behavioral traits like authentication requirements, rate limits, error handling, or the format of results (e.g., boolean, detailed match info). 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 is front-loaded with the core action and resource, making it easy to parse. Every part of the sentence earns its place by conveying essential information.
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 of a security-related tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., what the output looks like, error conditions) and usage context. For a tool that checks IPs in WAF sets, more information on permissions, scope, and result interpretation would be needed for an agent to use it 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 100%, with the parameter 'ip_address' fully documented in the schema. The description mentions 'IP address' but adds no additional meaning beyond what the schema provides (e.g., format examples like IPv4/IPv6, validation rules). With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate with extra insights.
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: 'Checks if an IP address exists in any WAF IP Set (Blocklists/Allowlists).' It specifies the verb ('checks'), resource ('IP address'), and scope ('any WAF IP Set'), but does not explicitly differentiate from sibling tools, which are mostly AWS resource listing tools with no direct overlap in functionality.
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, such as whether it applies to specific AWS regions or WAF configurations. The sibling tools are unrelated (e.g., list-based operations), so no explicit comparison is made.
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 it 'retrieves' anomalies, implying a read-only operation, but doesn't mention authentication requirements, rate limits, pagination, return format, or what constitutes an 'anomaly'. This leaves significant gaps for a tool that presumably returns structured anomaly 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 immediately conveys the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and is perfectly front-loaded with the essential information.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain what data is returned, how anomalies are structured, whether results are paginated, or any behavioral constraints. Given the complexity of cost anomaly data and the lack of structured output documentation, more context is needed for effective 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 100%, with both parameters clearly documented as date strings in YYYY-MM-DD format. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score of 3 for adequate coverage through the schema alone.
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 ('Retrieves') and resource ('cost anomalies detected by AWS Cost Anomaly Detection'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_cost_breakdown' or 'get_cost_by_service', but the specific focus on 'anomalies' provides inherent 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 like 'get_cost_breakdown' or 'get_recent_cost'. It mentions AWS Cost Anomaly Detection as the source, but doesn't specify use cases, prerequisites, or exclusions that would help an agent choose appropriately among cost-related 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. It states the tool predicts costs but doesn't mention whether this is a read-only operation, requires specific permissions, involves computational costs or rate limits, or what the output format looks like (e.g., time-series data, confidence intervals). For a prediction 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Predicts future costs for a specified time range.' It is front-loaded with the core purpose and wastes no words, making it easy for an agent to parse quickly. Every word earns its place.
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 of a forecasting tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the prediction output includes (e.g., point estimates, intervals), how accuracy or confidence is handled, or any behavioral traits like latency or data freshness. This leaves the agent with insufficient context for effective 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 mentions 'specified time range,' which aligns with the 'start_date' and 'end_date' parameters in the schema. However, with 100% schema description coverage, the schema already fully documents all four parameters, including their types, formats, enums, and defaults. The description adds minimal value beyond what the schema provides, meeting the baseline of 3.
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: 'Predicts future costs for a specified time range.' It uses a specific verb ('predicts') and resource ('future costs'), and while it doesn't explicitly distinguish from siblings like 'get_cost_breakdown' or 'get_recent_cost', the prediction focus is clear. However, it lacks explicit sibling differentiation, preventing a score of 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. With siblings like 'get_cost_breakdown', 'get_cost_anomalies', and 'get_recent_cost' available, there is no indication of when forecasting is appropriate compared to analyzing current or historical data. This leaves the agent without 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. It states 'Retrieves' which implies a read-only operation, but doesn't clarify authentication requirements, rate limits, error conditions, or what 'detailed information' entails (e.g., state, type, tags). This is inadequate for a 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 a single, well-structured sentence that gets straight to the point with zero wasted words. It's front-loaded with the core action and resource, making it highly efficient for quick comprehension by an AI agent.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'detailed information' includes (e.g., JSON structure, fields), behavioral aspects like permissions or errors, or how it differs from sibling tools. This leaves significant gaps for an agent to understand the tool's full context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the single 'instance_id' parameter. The description doesn't add any meaning beyond what's in the schema (e.g., format examples, validation rules, or where to find instance IDs). Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Retrieves') and resource ('detailed information about a specific EC2 instance'), making the purpose immediately understandable. It distinguishes from sibling tools like 'list_ec2_instances' by focusing on a single instance rather than listing multiple. However, it doesn't specify what 'detailed information' includes, 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. It doesn't mention prerequisites (e.g., needing an instance ID), contrast with 'list_ec2_instances' for bulk retrieval, or specify use cases like troubleshooting or monitoring. This leaves the agent without contextual usage cues.
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 the default date range and that costs are retrieved, but fails to describe critical aspects like response format, pagination, rate limits, authentication needs, or whether the operation is read-only. This leaves significant gaps for a cost 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and includes the default behavior, making it easy to parse quickly.
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 of cost data retrieval, no annotations, and no output schema, the description is incomplete. It lacks details on response structure, error handling, permissions, or how it differs from sibling cost tools, leaving the agent under-informed for effective 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 100%, so the schema already documents both parameters (start_date and end_date) with format details. The description adds marginal value by mentioning the default range ('last 7 days'), which isn't in the schema, but doesn't provide additional semantic context beyond what the schema covers.
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 ('Retrieves') and resource ('daily AWS costs') with scope ('for the specified date range'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like get_cost_breakdown or get_cost_by_service, 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 get_cost_breakdown or get_cost_forecast. It mentions a default date range but offers no context about prerequisites, use cases, or exclusions, leaving the agent with insufficient decision-making 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 the full burden of behavioral disclosure. It states the tool retrieves log events but doesn't mention critical details like whether it's read-only, what format the logs are returned in, if there are rate limits, or authentication requirements. 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.
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 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete for a tool that retrieves data. It doesn't explain what the return format looks like (e.g., structured logs, timestamps), potential limitations like pagination or time ranges, or error conditions. For a data retrieval tool with no structured output information, this leaves too many unknowns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters. The description doesn't add any additional semantic context beyond what the schema provides, such as examples or constraints. With high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Retrieves') and resource ('recent log events from a CloudWatch Log Group'), making the purpose understandable. However, it doesn't differentiate from the sibling tool 'search_cloudwatch_logs', which appears to be a related alternative for log operations, leaving some ambiguity 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?
No guidance is provided on when to use this tool versus alternatives like 'search_cloudwatch_logs' or other log-related tools. The description lacks context about prerequisites, such as needing specific permissions or when this tool is preferred over others for accessing logs.
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 it 'retrieves' data (implying read-only), but doesn't specify authentication requirements, rate limits, data freshness, or what format the utilization percentages are returned in. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.
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 immediately conveys the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool and front-loads the essential information.
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 no annotations and no output schema, the description is incomplete for a tool that presumably returns complex utilization data. It doesn't explain what the output looks like (e.g., time-series data, aggregated percentages), nor does it provide context about RI types or scopes. For a data retrieval tool with rich sibling tools, this leaves too much unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both required date parameters with format specifications. The description doesn't add any parameter semantics beyond what the schema already provides (no explanation of date range constraints or how utilization is calculated across that range). The baseline score of 3 is appropriate when the schema does all the work.
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 ('Retrieves') and resource ('Reserved Instance (RI) utilization percentages'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'get_savings_plans_utilization' or other cost-related tools, 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. There's no mention of prerequisites, context for when RI utilization data is needed, or comparison to other cost/usage tools in the sibling list. The agent must infer usage from the 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 the full burden of behavioral disclosure. It states the tool 'retrieves' data, implying a read-only operation, but doesn't specify permissions required, rate limits, response format, or whether it returns aggregated or detailed percentages. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose, making it easy to parse quickly, which is ideal for conciseness in a tool definition.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the utilization percentages represent (e.g., overall, by plan, time granularity), how results are structured, or any behavioral constraints. For a financial data tool with no structured support, this leaves significant gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters as date strings in YYYY-MM-DD format. The description adds no parameter semantics beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without adding 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 clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('Savings Plans utilization percentages'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'get_reservation_utilization' or 'get_cost_breakdown' that might retrieve related financial data, 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. With many sibling tools for cost and utilization data (e.g., 'get_reservation_utilization', 'get_cost_breakdown'), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on 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 the full burden of behavioral disclosure. It states the action ('Retrieves') but does not clarify aspects like whether this is a read-only operation, potential rate limits, authentication requirements, or the format of returned data. This leaves significant gaps for an agent to understand how the tool behaves in practice.
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, direct sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the main action and resource, making it easy to parse and understand quickly, which is ideal for conciseness.
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 lack of annotations and output schema, the description is insufficient for a tool with 4 parameters and no behavioral context. It does not address return values, error handling, or operational constraints, making it incomplete for an agent to reliably use this tool in complex scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, providing clear details for all parameters (e.g., ARN, metric name, scope, time window). The description adds no additional semantic context beyond what the schema already specifies, such as examples or usage notes, so it meets the baseline for adequate but not enhanced 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 verb ('Retrieves') and resource ('sampled requests from a Web ACL'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list_web_acls' or 'list_access_denied_events', which might offer related but distinct functionality, 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, such as 'list_access_denied_events' or other AWS WAF-related tools. It lacks context on prerequisites, typical use cases, or exclusions, leaving the agent to infer usage based on the tool name and parameters 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 but offers minimal information. It mentions 'recent' events but doesn't define the time range, specify whether results are paginated, indicate authentication requirements, or describe the return format. For a security monitoring tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 that gets straight to the point without unnecessary words. It's appropriately sized for a simple list operation, though it could potentially benefit from a second sentence to clarify scope or differentiation from sibling tools.
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 lack of annotations and output schema, the description is insufficiently complete. A security event listing tool should ideally specify time ranges, result format, authentication requirements, or any filtering criteria beyond just 'Access Denied or Unauthorized.' The description leaves too many operational questions unanswered for effective tool selection and 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?
The input schema has 100% description coverage, with the single parameter 'limit' clearly documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.
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 ('Lists') and the resource ('Access Denied or Unauthorized events from CloudTrail'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from sibling tools like 'list_recent_cloudtrail_events' or 'list_cloudtrail_changes', which could cause confusion about when to use this specific filtered list versus other CloudTrail-related 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 multiple CloudTrail-related sibling tools (list_recent_cloudtrail_events, list_cloudtrail_changes), there's no indication whether this tool provides a filtered subset, different time ranges, or serves a distinct security monitoring purpose. The agent must infer usage context from the 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 the full burden of behavioral disclosure. While it mentions the tool lists 'write/mutation events,' it doesn't cover critical aspects like authentication requirements, rate limits, pagination, error conditions, or what the output format looks like. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that clearly states the tool's purpose without unnecessary words. It's front-loaded with the core functionality and avoids redundancy, 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of listing cloud trail changes (which involves filtering and event types), no annotations, and no output schema, the description is insufficient. It doesn't explain the return format, error handling, or how events are structured, leaving the agent with incomplete context for proper 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 100%, so the schema already documents all four parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema, such as examples, constraints, or interactions between parameters. This meets the baseline for high 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?
The description clearly states the tool's function: 'Lists write/mutation events (Create, Update, Delete) for a specific resource or service.' It specifies the verb ('Lists'), resource ('write/mutation events'), and scope ('for a specific resource or service'). However, it doesn't explicitly differentiate from sibling tools like 'list_recent_cloudtrail_events' or 'list_access_denied_events', which might offer similar functionality.
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 'list_recent_cloudtrail_events' or 'list_access_denied_events', nor does it specify prerequisites, exclusions, or typical use cases. The agent must infer usage from the 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions optional filtering by state but fails to describe critical traits: whether this is a read-only operation (implied by 'Lists' but not explicit), potential rate limits, pagination behavior, required authentication, or output format. For a tool with zero 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose and key feature. There is no wasted language or redundancy, making it efficient and easy to parse. This earns a perfect score for conciseness and structure.
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 list operation with filtering) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like safety (read-only vs. destructive), authentication needs, rate limits, or return values. While it mentions filtering, it fails to provide a holistic view needed for effective use, resulting in a low score.
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 value beyond the input schema, which has 100% coverage for its single parameter ('state'). It mentions 'optionally filtering by state,' aligning with the schema's description, but doesn't provide additional context like default behavior if omitted or interaction with other filters. With high schema coverage, the baseline is 3, as the description doesn't significantly enhance 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 with a specific verb ('Lists') and resource ('CloudWatch alarms'), making it immediately understandable. It distinguishes itself from siblings by focusing on alarms rather than other AWS resources like instances, buckets, or logs. However, it doesn't explicitly differentiate from potential similar tools (e.g., 'get_metric_statistics' for metrics vs. alarms), keeping it at a 4 rather than a 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 minimal guidance with 'optionally filtering by state,' but offers no explicit context on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., AWS permissions), compare to siblings like 'search_cloudwatch_logs' for related data, or specify scenarios (e.g., monitoring vs. troubleshooting). This lack of detailed when-to-use guidance results in a score of 2.
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 lists services but doesn't describe behavioral traits such as pagination, rate limits, authentication requirements, error handling, or output format. For a read operation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Lists services in a specific ECS cluster.' It is front-loaded with the core action and resource, with zero wasted words or redundancy. This makes it easy for an agent to parse and understand quickly.
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 one parameter) and the absence of annotations and output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., pagination, error handling) and doesn't compensate for the missing output schema by describing return values. This leaves gaps for an agent to use the tool 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?
The input schema has 100% description coverage, with the single parameter 'cluster' documented as 'The name or ARN of the ECS cluster.' The description adds no additional meaning beyond this, such as examples or constraints. According to the rules, with high schema coverage (>80%), the baseline score is 3, which is appropriate here.
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: 'Lists services in a specific ECS cluster.' It specifies the verb ('Lists') and resource ('services in a specific ECS cluster'), making the action and target unambiguous. However, it doesn't distinguish this tool from its sibling 'list_ecs_clusters' or other listing tools, 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. It doesn't mention prerequisites (e.g., needing cluster access), exclusions, or comparisons to similar tools like 'list_ecs_clusters' or other AWS service listing tools. This lack of contextual guidance leaves the agent to infer usage scenarios independently.
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 'recent' and 'high-severity' but lacks details on what 'recent' means (e.g., last 24 hours), whether results are paginated, authentication requirements, rate limits, or error handling. This is inadequate for a tool that likely interacts with AWS services.
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 that front-loads key information ('Lists recent high-severity GuardDuty findings'). It avoids redundancy but could be slightly more informative without losing conciseness, such as by specifying a default timeframe.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain return values (e.g., format of findings), error conditions, or behavioral nuances like pagination or AWS region dependencies. Given the complexity of security findings, more context is needed 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?
The input schema has 100% description coverage, clearly documenting both parameters with defaults. The description adds minimal value by implying 'high-severity' relates to the 'severity' parameter, but doesn't explain severity scales (e.g., 1-10) or clarify 'recent' beyond the schema. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lists') and resource ('GuardDuty findings') with a specific scope ('recent high-severity'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_security_groups' or 'list_open_security_groups' that might also relate to security findings, leaving room for ambiguity in a crowded toolset.
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 mentions 'recent high-severity' but doesn't specify timeframes, compare to other listing tools, or indicate prerequisites like required AWS permissions, 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Lists NAT Gateways' but doesn't cover critical aspects like whether this is a read-only operation, if it requires specific permissions, pagination behavior, rate limits, or what happens on errors. This leaves significant gaps for an agent to understand how to use it safely and 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 function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 lack of annotations and output schema, the description is incomplete for a tool that likely returns a list of resources. It doesn't explain the return format, error handling, or behavioral traits, which are crucial for an agent to use it correctly in a cloud environment with many 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?
The input schema has 100% description coverage, with the single parameter 'vpc_id' documented as 'Optional: Filter by VPC ID.' The description doesn't add any meaning beyond this, such as format examples or usage context, so it meets the baseline score of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('NAT Gateways') with specific attributes ('their state and public IP'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_vpcs' or 'list_subnets' beyond the resource type, 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?
The description provides no guidance on when to use this tool versus alternatives, such as other listing tools for AWS resources or filtering options. It mentions no prerequisites, exclusions, or context for selection among the many sibling tools available.
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 lists access keys based on an age threshold, but doesn't cover critical aspects like whether this is a read-only operation, if it requires specific IAM permissions, what the output format looks like, or if there are rate limits. For a 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Lists access keys older than 90 days (or specified days).' It's front-loaded with the core purpose and includes the key detail about the parameter, with zero wasted words. This makes 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.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the output contains (e.g., key IDs, creation dates, associated users), behavioral traits like safety or permissions, or usage context. For a tool that likely interacts with IAM and could have security implications, this leaves significant gaps for an agent to operate 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?
The input schema has 100% description coverage, with the 'days' parameter clearly documented as 'Number of days threshold (default: 90).' The description adds minimal value by mentioning '90 days (or specified days),' which aligns with but doesn't expand beyond the schema. With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't provide additional parameter insights.
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: 'Lists access keys older than 90 days (or specified days).' It specifies the verb ('Lists'), resource ('access keys'), and scope ('older than 90 days or specified days'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'list_iam_users' or other list tools, which would require a 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 any prerequisites, context for usage, or comparisons with sibling tools (e.g., how it differs from general IAM listing tools). This leaves the agent without clear direction on 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?
With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the action is a list operation, implying read-only behavior, but doesn't disclose critical details like pagination, rate limits, authentication requirements, error conditions, or what 'DNS records' specifically includes (e.g., types A, CNAME). This leaves significant gaps for an agent to understand operational constraints.
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 front-loads the core purpose without unnecessary words. It directly states the tool's function without redundancy or fluff, making it easy to parse quickly.
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 no annotations and no output schema, the description is incomplete for a tool that likely returns complex DNS data. It doesn't explain return values (e.g., record types, values, TTLs), error handling, or behavioral traits like pagination. For a list operation with potential rich output, more context is needed to guide an 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 100%, with the single parameter 'hosted_zone_id' fully documented in the schema. The description adds no additional meaning beyond implying this ID is required for listing records, which is already clear from the schema. This meets the baseline of 3 when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lists') and resource ('DNS records for a given hosted zone'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_hosted_zones' or 'list_route_tables', which would require mentioning the specific DNS context or record types to achieve 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a hosted zone ID first), exclusions (e.g., not for listing zones themselves), or comparisons to siblings like 'list_hosted_zones'. Usage is implied by the parameter but not explicitly 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'recent scaling activities' but doesn't specify time ranges, pagination, rate limits, authentication needs, or what constitutes 'recent.' This leaves significant gaps in understanding 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 a single, efficient sentence that front-loads the core purpose without unnecessary details. However, it could be slightly more structured by explicitly mentioning the parameter or output expectations to improve 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 no annotations and no output schema, the description is incomplete for a tool that likely returns complex data (e.g., lists of activities). It doesn't cover return formats, error handling, or behavioral nuances, leaving 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting the single required parameter. The description adds no additional meaning beyond the schema, such as format examples or constraints, so it meets the baseline for high schema coverage without compensating 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 clearly states the tool's purpose with a specific verb ('Describes') and resource ('recent scaling activities for an Auto Scaling Group'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_auto_scaling_groups' or other monitoring tools, which would require a 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, such as how it differs from general monitoring tools or when 'recent' scaling activities are relevant. It lacks context on prerequisites or exclusions, leaving usage 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. While 'Lists' implies a read-only operation, the description doesn't disclose important behavioral aspects like whether this returns all security groups across all regions/VPCs, whether results are paginated, what format the output takes, or any rate limits or authentication requirements.
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 - a single sentence that states exactly what the tool does with zero wasted words. It's front-loaded with the core functionality and contains no unnecessary elaboration.
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 tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what information is returned about security groups, how results are structured, whether there are limitations on what's returned, or how this differs from the similar 'list_open_security_groups' tool. The minimal description leaves too many unanswered questions for effective tool 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?
Schema description coverage is 100%, so the schema already fully documents the single optional parameter (vpc_id). The description adds no additional parameter information beyond what's in the schema, which is acceptable given the high schema coverage, resulting in the baseline score of 3.
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 ('Lists') and resource ('all security groups'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from its sibling 'list_open_security_groups' - both appear to list security groups, making the differentiation unclear.
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 about when to use this tool versus alternatives. With a sibling tool called 'list_open_security_groups' that likely serves a similar purpose, there's no indication of when to choose one over the other, nor any context about prerequisites 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?
No annotations are provided, so the description carries full burden. It states the action ('Lists') but lacks behavioral details such as pagination, rate limits, authentication requirements, or output format. This is a significant gap for a tool with no structured safety hints.
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 front-loads the core purpose and includes essential scope details, making it easy to parse without unnecessary elaboration.
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 no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., read-only nature, error handling) and return values, which are critical for an agent to use the tool effectively in a cloud management context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'scope' fully documented in the schema (enum values and default). The description adds minimal value by mentioning 'Global/CloudFront or Regional', which aligns with the schema but doesn't provide additional semantics beyond it.
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 ('Lists') and resource ('Web ACLs'), specifying the scope options (Global/CloudFront or Regional). It distinguishes the tool's focus on Web ACLs from siblings like list_cloudfront_distributions or list_security_groups, 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. While it implies usage for listing Web ACLs, it doesn't mention prerequisites, context (e.g., AWS WAF setup), or compare to siblings like get_waf_sampled_requests, leaving the agent to infer 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the search functionality but doesn't describe important behavioral traits like whether this is a read-only operation (implied but not stated), potential rate limits, authentication requirements, time window defaults, or what the output format looks like. The description is too minimal for a tool with 6 parameters and no output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that gets straight to the point without unnecessary words. It's front-loaded with the core functionality. However, for a tool with 6 parameters and no annotations, this brevity comes at the cost of completeness rather than representing optimal 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 tool's complexity (6 parameters, no annotations, no output schema, 67% schema coverage), the description is insufficiently complete. It doesn't explain the tool's behavior, output format, error conditions, or relationship to sibling tools. For a search tool that likely returns structured log data, the description should provide more context about what the agent can expect from using this 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?
The description mentions the filter pattern parameter with examples ('ERROR', 'Exception'), which adds some semantic context beyond the schema's description. However, with 67% schema description coverage and 6 total parameters, it doesn't adequately explain the purpose of other key parameters like log_group_name, limit, hours, start_time, or end_time. The description provides marginal value but doesn't compensate for the schema's coverage 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 tool's purpose with a specific verb ('Search') and resource ('CloudWatch logs'), and includes the key mechanism ('using a filter pattern'). It distinguishes itself from sibling tools like 'get_recent_logs' by emphasizing pattern-based searching rather than simple retrieval. However, it doesn't explicitly differentiate from potential overlapping tools beyond the basic function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_recent_logs' or other logging-related tools. It mentions the filter pattern mechanism but doesn't specify scenarios where this is preferred over simpler log retrieval or other AWS monitoring tools. No exclusions or prerequisites 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 describes a read-only operation ('Lists') but does not mention permissions, rate limits, pagination, or response format. The description is minimal and lacks critical behavioral details 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.
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 is front-loaded with the core action and resource, making it easy to understand quickly. Every part of the sentence contributes to clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (a read operation with one parameter) and lack of annotations and output schema, the description is minimally complete. It covers the basic purpose but misses behavioral details like permissions or response structure. For a tool with no annotations, it should provide more context 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 100%, with the single parameter 'account_id' fully documented in the schema. The description does not add any parameter-specific information beyond what the schema provides, such as format examples or constraints. The baseline score of 3 reflects adequate coverage by the schema alone.
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: 'Lists all AWS Budgets along with their status, limits, and current spend.' It specifies the verb ('Lists'), resource ('AWS Budgets'), and scope ('all'), but does not explicitly differentiate from sibling tools like 'get_cost_breakdown' or 'get_cost_forecast', which are related but not direct alternatives for listing budgets.
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 sibling tools or contexts where this tool is preferred, such as for budget monitoring versus cost analysis. Usage is implied by the purpose but lacks explicit when/when-not 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves cost data but doesn't mention critical aspects like whether it requires specific AWS permissions, if it's read-only, how it handles large date ranges, or what the output format looks like. For a data retrieval tool with no 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a simple retrieval tool with well-documented 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 low complexity (2 parameters, no nested objects) and high schema coverage, the description is adequate but incomplete. It lacks output schema information and behavioral context, which is notable since no annotations are provided. It's minimally viable but has clear gaps in usage 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?
The input schema has 100% description coverage, clearly documenting both parameters (start_date and end_date) with format details. The description adds no additional parameter information beyond what's in the schema, so it meets the baseline score of 3 where the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Retrieves') and resource ('AWS costs broken down by service'), making it easy to understand what it does. However, it doesn't explicitly distinguish itself from sibling tools like 'get_cost_breakdown' or 'get_recent_cost', which might have overlapping functionality, so it doesn't reach 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. With sibling tools like 'get_cost_breakdown' and 'get_recent_cost' present, there's no indication of differences in scope, granularity, or context, leaving the agent to guess based on names 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. It states 'Retrieves' which implies a read operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, pagination, error conditions, or what 'statistics' specifically includes (e.g., percentiles, counts). This leaves significant gaps for a tool with 7 parameters.
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 states the core purpose without unnecessary words. It's appropriately sized and front-loaded, with every word earning 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 7 parameters, no annotations, and no output schema, the description is minimally adequate but lacks completeness. It doesn't explain return values, error handling, or behavioral constraints, which are important for a statistics retrieval tool. However, the clear purpose and concise structure provide a basic foundation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all 7 parameters. The description adds no parameter-specific information beyond what's in the schema, but doesn't need to compensate for gaps. Baseline 3 is appropriate when the schema does all the work.
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 ('Retrieves') and resource ('statistics for a specific CloudWatch metric'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_cloudwatch_alarms' or 'search_cloudwatch_logs', 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. With many sibling tools in the AWS/CloudWatch space, there's no mention of prerequisites, typical use cases, or comparisons to tools like 'list_cloudwatch_alarms', leaving the agent with insufficient context for 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?
No annotations are provided, so the description carries full burden. It states the tool retrieves health data, implying a read-only operation, but doesn't disclose behavioral traits like authentication needs, rate limits, error handling, or what 'health' entails (e.g., metrics, status). This leaves gaps for an AI agent.
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 front-loads the core purpose without unnecessary details. It earns its place by directly stating what the tool does, making it well-structured 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 no annotations and no output schema, the description is minimal but covers the basic purpose. For a tool with one parameter and high schema coverage, it's adequate but lacks depth on behavior or output, leaving room for improvement in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'target_group_arn' clearly documented in the schema. The description adds no additional meaning beyond implying the ARN specifies the Target Group, aligning with the baseline for high 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?
The description clearly states the action ('Retrieves') and resource ('health of targets in a specified Target Group'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'list_target_groups' or 'get_service_health', which reduces 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. While the description implies it's for health monitoring of targets, there's no mention of prerequisites, related tools, or scenarios where 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 the full burden. It mentions the tool lists groups and includes capacity settings, but lacks critical behavioral details: whether it requires specific AWS permissions, if it paginates results, what format the output takes, or any rate limits. For a read operation 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 that front-loads the core action and resource. Every word contributes meaning without waste, making it easy to parse quickly.
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 no annotations and no output schema, the description is incomplete for a tool that likely returns complex data (Auto Scaling Groups with capacity settings). It doesn't explain the return structure, potential errors, or behavioral constraints, leaving significant gaps for the agent to operate effectively.
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 has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter details (as there are none), which is appropriate. Baseline is 4 for zero parameters, 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 verb ('Lists') and resource ('Auto Scaling Groups') with additional detail about what information is included ('with their capacity settings'). It distinguishes from generic list operations by specifying the resource type, though it doesn't explicitly differentiate from potential similar tools (like 'list_scaling_activities' which is a sibling).
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 context for selection. It doesn't mention any of the many sibling tools (e.g., 'list_scaling_activities', 'list_ec2_instances') that might be relevant in similar contexts, leaving the agent to infer usage based on 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 mentions filtering and defaults but fails to describe critical aspects like pagination, rate limits, authentication needs, or what 'recent' means beyond the hours parameter. This leaves significant gaps in understanding 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose and includes key details without waste. Every word contributes to understanding, making it appropriately sized and well-structured for quick comprehension.
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 output schema, no annotations), the description is adequate but incomplete. It covers the basic action and parameters but lacks behavioral context (e.g., response format, limitations), which is needed for a read operation without annotations to fill those 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?
The input schema has 100% description coverage, so the schema already documents both parameters thoroughly. The description adds minimal value by mentioning the optional state filter and its default, but doesn't provide additional context beyond what's in the schema, aligning with the baseline for high 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?
The description clearly states the tool's purpose with a specific verb ('Lists') and resource ('recent backup jobs'), making it immediately understandable. However, it doesn't differentiate from sibling tools like 'list_ec2_instances' or 'list_s3_buckets' beyond the resource type, which keeps it from 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 mentions optional filtering by state but doesn't explain prerequisites, typical use cases, or how it relates to other list tools in the server, leaving the agent with minimal context for 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 mentions listing stacks and their status, but fails to describe key traits like pagination behavior, authentication requirements, rate limits, or what 'status' entails. This leaves significant gaps for a tool that likely interacts with AWS CloudFormation.
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 front-loads the core action without any wasted words. It's appropriately sized for a simple listing tool, making it highly concise and well-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?
Given the complexity of AWS CloudFormation, no annotations, and no output schema, the description is incomplete. It lacks details on output format, error handling, or behavioral context, making it insufficient for an agent to fully understand the tool's operation without additional assumptions.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 for adequately handling the lack 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 verb ('Lists') and resource ('CloudFormation stacks and their status'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_ec2_instances' or 'list_s3_buckets' beyond specifying the AWS service, which is adequate but not exceptional.
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, such as filtering criteria, prerequisites, or comparisons with other listing tools. It lacks explicit context or exclusions, leaving usage entirely implicit.
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. 'Lists DynamoDB tables' implies a read-only operation but doesn't specify whether this requires specific IAM permissions, returns all tables or just those accessible to the caller, includes pagination details, or provides any metadata about the tables. For a cloud resource listing 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 essential information and perfectly sized for its purpose.
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 cloud resource listing tool with no annotations and no output schema, the description is inadequate. It doesn't explain what information is returned (just table names? ARNs? status?), whether results are paginated, what permissions are required, or any AWS region/account context. The description should provide more operational 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 tool has zero parameters (schema coverage 100%), so no parameter documentation is needed. The description doesn't attempt to explain nonexistent parameters, which is appropriate. A baseline of 4 is correct for zero-parameter 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 clearly states the verb ('Lists') and resource ('DynamoDB tables'), making the purpose immediately understandable. It doesn't differentiate from sibling tools, but since all siblings are distinct AWS resource listing operations (like list_s3_buckets, list_ec2_instances), the lack of differentiation is less critical here.
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 the sibling tools are all distinct AWS resource types, there's no explicit mention of when this specific listing operation is appropriate versus other AWS inventory 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 the full burden of behavioral disclosure. It mentions the region scope but does not cover critical aspects like authentication requirements, rate limits, pagination behavior, error handling, or the format of returned data (e.g., cluster names, statuses). This leaves significant gaps for a tool that interacts with AWS services.
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 front-loads the core purpose ('Lists EKS clusters') and adds necessary scope ('in the current region'). There is no wasted verbiage or unnecessary elaboration, making it highly concise and well-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?
Given the lack of annotations and output schema, the description is incomplete. It does not address behavioral traits (e.g., authentication, pagination) or output details (e.g., what data is returned), which are essential for an AWS listing tool. While concise, it fails to provide sufficient context for safe and effective use by 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?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not add parameter details, and the baseline score is 4 as it avoids redundancy while confirming the tool operates without inputs in the current region 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 action ('Lists') and resource ('EKS clusters'), specifying the scope as 'in the current region'. However, it does not differentiate from sibling tools like 'list_ecs_clusters' or 'list_ec2_instances', which follow similar naming patterns but target different AWS 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 on when to use this tool versus alternatives. The description lacks context about prerequisites (e.g., AWS authentication, region configuration) or comparisons to other listing tools, such as 'list_ecs_clusters' for ECS resources or 'list_ec2_instances' for EC2 instances.
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 mentions listing certificates but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or what 'lists' entails (e.g., format, completeness). For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 front-loads the core functionality without unnecessary words. It's appropriately sized for a simple tool with one parameter, earning full marks 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 low complexity (one optional parameter, no output schema, no annotations), the description is minimally adequate. However, it lacks details on output format (e.g., what data is returned) and behavioral context, which would be helpful for an agent to use it effectively. It meets basic needs 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?
The input schema has 100% description coverage, with the 'days' parameter documented as 'Number of days threshold (default: 30).' The description adds minimal value by mentioning 'specified days,' which aligns with the schema but doesn't provide additional semantics like examples or edge cases. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('ACM certificates expiring within the specified days'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_certificates' (which doesn't exist in the provided list), 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 (e.g., other AWS certificate-related tools not listed here) or any prerequisites. It simply states what it does without context about appropriate scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('Lists') but doesn't describe return format, pagination, rate limits, permissions required, or any side effects. This leaves significant gaps in understanding how the tool behaves in practice.
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 function without any fluff. It's front-loaded with the core action and resource, making it easy to parse and understand immediately.
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 no annotations and no output schema, the description is incomplete for a tool that likely returns structured data. It doesn't explain what 'Lists' entails (e.g., format, scope, limitations), leaving the agent without crucial context for proper 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?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose, which aligns with the baseline expectation for parameterless 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 clearly states the verb ('Lists') and resource ('all Route53 Hosted Zones'), making the tool's purpose immediately understandable. It distinguishes itself from siblings like 'list_record_sets' by specifying the resource type, though it doesn't explicitly contrast with other list tools beyond that.
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, leaving the agent to infer usage based on the resource name alone without explicit 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 only states what the tool does, not how it behaves. It doesn't disclose whether this is a read-only operation, if it requires specific permissions, what format the output takes, or any pagination/rate limiting considerations.
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 function with zero waste. It's appropriately sized for a simple listing tool and front-loads the essential information.
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 tool with no annotations and no output schema, the description is insufficient. It doesn't explain what information is returned about the gateways and attachments, nor does it provide behavioral context about permissions, scope, or limitations 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.
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 empty input. The description appropriately doesn't add parameter information, maintaining focus on the tool's purpose rather than redundant 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 action ('Lists') and resource ('Internet Gateways and their attachments'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'list_nat_gateways' or 'list_vpcs' beyond naming the specific AWS 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, or exclusions, leaving the agent to infer usage from the tool name alone among many similar 'list_' 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. It mentions the tool lists data but does not disclose behavioral traits like whether it's read-only, if it requires specific permissions, rate limits, or pagination. This is a significant gap 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 a single, efficient sentence that front-loads the key information without any wasted words. It is appropriately sized for the tool's purpose, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral aspects and usage context, which are needed for full completeness, especially with no annotations to fill 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?
The schema description coverage is 100%, so the input schema fully documents the 'load_balancer_arn' parameter. The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, resulting in the baseline score of 3.
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 ('Lists') and the resources ('listeners and routing rules (host, path) for a specified Load Balancer'), making the purpose evident. However, it does not explicitly differentiate from sibling tools like 'list_load_balancers' or 'list_target_groups', which reduces the score from a 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 specifies the context ('for a specified Load Balancer') but provides no guidance on when to use this tool versus alternatives, such as other list tools for related AWS resources. There are no explicit exclusions or recommendations for sibling tools, leaving usage 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 the full burden of behavioral disclosure. It states the action ('Lists') but does not cover critical aspects like pagination, rate limits, authentication needs, output format, or whether it's a read-only operation. This leaves significant gaps in understanding how the tool behaves in practice.
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 waste. It is front-loaded and appropriately sized for a simple list operation, making it easy to parse and understand quickly.
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 list operation with no parameters) and lack of annotations and output schema, the description is incomplete. It does not address behavioral traits like output format, pagination, or error handling, which are essential for effective use. This leaves the agent with insufficient context to invoke the tool reliably.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter information, which is appropriate, and it implies no filtering or scoping, aligning with the empty schema. This meets the baseline for tools with no 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 ('Lists') and resource ('all Application and Network Load Balancers'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list_target_groups' or 'list_ec2_instances', which might also relate to load balancers in a broader context, 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, such as other list tools for related resources or filtering options. It lacks context on prerequisites, timing, or comparisons to sibling tools, leaving usage unclear 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 full burden for behavioral disclosure. While 'Lists' implies a read operation, it doesn't specify authentication requirements, rate limits, pagination behavior, or what 'recent' means temporally. 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that states the purpose clearly without unnecessary words. It's appropriately sized for a listing tool and front-loads the essential information.
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 listing tool with no output schema and no annotations, the description provides basic purpose but lacks important context about authentication, temporal scope of 'recent', response format, or error handling. It's minimally viable 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?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter semantics.
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 ('Lists') and resource ('recent CloudTrail events'), and provides specific purpose context ('to track console access and changes'). However, it doesn't explicitly differentiate from sibling tools like 'list_cloudtrail_changes' or 'list_access_denied_events', which might have overlapping domains.
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 multiple sibling tools that might overlap (e.g., 'list_cloudtrail_changes', 'list_access_denied_events', 'get_recent_logs'), but the description offers no comparison or context for 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 full burden for behavioral disclosure. It states this is a list operation, implying read-only behavior, but doesn't mention any constraints like permissions needed, rate limits, pagination behavior, or what happens when no VPC filter is provided. For a tool with zero annotation coverage, this leaves significant behavioral questions unanswered.
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 functionality without unnecessary words. It's appropriately sized for a simple list operation and front-loads the essential information.
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 list tool with one optional parameter and no output schema, the description is minimally adequate. However, with no annotations and no output schema, it should ideally provide more context about what the response contains (beyond mentioning 'routes and associations') and any behavioral constraints. The description meets basic requirements but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the single parameter 'vpc_id' clearly documented as optional for filtering. The description doesn't add any parameter information beyond what the schema already provides, so the baseline score of 3 is appropriate given the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('route tables') with additional detail about what information is included ('with their routes and associations'). This is specific and actionable, though it doesn't explicitly differentiate from sibling tools beyond the obvious resource focus.
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 sibling list includes many other 'list_' tools for different AWS resources, the description doesn't mention any specific context, prerequisites, or exclusions for using this particular 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?
With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose behavioral traits like whether this requires specific IAM permissions, if it's paginated, rate limits, what format the output takes, or whether it's a read-only operation (though implied by 'Lists').
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 states exactly what the tool does with zero wasted words. It's appropriately sized for a simple listing operation and front-loads the core 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?
For a simple listing tool with one well-documented parameter but no annotations or output schema, the description provides the minimum viable information. However, it lacks context about permissions, output format, and operational constraints that would be helpful given the AWS context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents the single parameter. The description doesn't add any parameter-specific context beyond what's in the schema, maintaining the baseline score for high 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?
The description clearly states the verb ('Lists') and resource ('all S3 buckets in the AWS account'), making the purpose immediately understandable. It distinguishes from siblings by specifying S3 buckets, though it doesn't explicitly differentiate from other list_* tools 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, permissions needed, or contextual triggers for selecting this tool over other AWS listing operations.
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 'Lists all SNS topics' but doesn't disclose behavioral traits such as pagination, rate limits, authentication requirements, or what 'all' entails (e.g., region-specific, account-wide). This is a significant gap 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 a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple list tool, making it easy to parse quickly.
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 simplicity (0 parameters, no output schema) and lack of annotations, the description is incomplete. It doesn't address behavioral aspects like scope, pagination, or error handling, which are important for an agent to use it correctly in a cloud environment.
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 no parameter documentation is needed. The description doesn't add parameter semantics, but this is appropriate given the lack of parameters, 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 'Lists all SNS topics' clearly states the verb ('Lists') and resource ('SNS topics'), making the tool's purpose immediately understandable. It distinguishes from siblings by specifying SNS topics, though it doesn't explicitly differentiate from other list tools 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 use, or comparison with other list tools in the sibling set (e.g., list_s3_buckets, list_lambda_functions).
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 mentions the output includes 'availability zones and available IP counts', which adds some behavioral context beyond a simple list. However, it doesn't disclose critical traits like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or error conditions. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.
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 front-loads the core purpose ('Lists subnets') and adds clarifying details ('with availability zones and available IP counts'). There's no wasted verbiage or redundancy, making it highly concise and well-structured for quick comprehension.
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 (one optional parameter, no output schema, no annotations), the description is minimally adequate. It specifies what data is returned, which helps contextualize the output. However, without annotations or an output schema, it lacks details on behavioral aspects like safety, performance, or error handling, leaving room for improvement in completeness for agent 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?
The input schema has 100% description coverage, with the single parameter 'vpc_id' documented as 'Optional: Filter by VPC ID.' The description doesn't add any parameter-specific information beyond what the schema provides. Since schema coverage is high, the baseline score of 3 is appropriate—the description doesn't compensate but doesn't need to given the schema's completeness.
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 ('Lists') and resource ('subnets'), and specifies what information is included ('with availability zones and available IP counts'). It distinguishes this from generic listing by mentioning the specific data fields returned, though it doesn't explicitly differentiate from sibling tools like 'list_vpcs' or 'list_security_groups' 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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for usage, or compare it to other listing tools in the sibling set (e.g., 'list_vpcs' for VPCs or 'list_security_groups' for security groups). The agent must infer usage based on 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 but only states the basic action. It doesn't disclose behavioral traits like whether results are paginated, time-bound, require specific permissions, or include rate limits. 'Lists recent open events' implies read-only and non-destructive, but lacks detail on what 'recent' means or output format.
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 wasted words. It's front-loaded with the core purpose and 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?
For a zero-parameter tool with no annotations and no output schema, the description is minimally adequate. It states what the tool does but lacks context about output format, time ranges, or AWS account scope. Given the simplicity, it's complete enough to be functional but leaves gaps for effective agent 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?
The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description doesn't add parameter semantics, but that's appropriate given the lack of parameters, warranting a baseline score above minimum.
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 ('Lists') and resource ('recent open events from AWS Health Dashboard'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'list_cloudwatch_alarms' or 'list_guardduty_findings' which also list AWS resources, 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?
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 sibling tools that might serve similar monitoring purposes in AWS.
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 the output includes 'domain names and status' but doesn't cover pagination, rate limits, authentication requirements, error conditions, or whether this is a read-only operation. 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 functionality without unnecessary words. It's appropriately sized and front-loaded with the essential information.
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 list tool with no parameters and no output schema, the description provides basic functionality but lacks details about output format, pagination, or behavioral constraints. Given the absence of annotations and output schema, it should provide more context about what to expect from the 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 zero parameters with 100% schema description coverage, so the schema already fully documents the parameter situation. The description appropriately doesn't discuss parameters, which is correct for a parameterless tool, earning a baseline 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 tool's purpose with a specific verb ('Lists') and resource ('CloudFront distributions'), including what information is returned ('domain names and status'). It doesn't explicitly differentiate from sibling tools, but the resource specificity makes its purpose clear.
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 contextual constraints. It simply states what the tool does without addressing usage scenarios or comparisons with other 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 mentions what fields are shown but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, error conditions, or whether this is a read-only operation. The description is minimal and lacks critical 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads key information (action, resource, scope, output). Every word earns its place with zero wasted content, making it easy to parse quickly.
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 listing tool with no annotations and no output schema, the description is incomplete. It doesn't explain the return format, pagination, error handling, or how the optional parameter affects behavior. Given the complexity of AWS EC2 operations and lack of structured fields, more context is needed for effective 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 100%, so the schema already documents the optional 'region' parameter. The description adds no additional parameter semantics beyond implying regional scope with 'current region', which aligns with but doesn't enhance the schema. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lists'), resource ('EC2 instances'), scope ('in the current region'), and specific output fields ('ID, type, state, and public IP'). It distinguishes from sibling tools like 'get_instance_details' by focusing on listing rather than detailed 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?
No guidance is provided on when to use this tool versus alternatives like 'get_instance_details' or other listing tools. The description mentions 'current region' but doesn't explain how this interacts with the optional 'region' parameter or when to override defaults.
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 the output includes 'status and running task counts', which adds some context about what data is returned, but fails to cover critical aspects like pagination, rate limits, authentication requirements, error handling, or whether it lists all clusters or requires filtering. This leaves significant gaps for a tool in a cloud environment.
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, well-structured sentence that front-loads the core action and resource, followed by specific output details. It wastes no words and is appropriately sized for a simple list tool, earning full marks 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 low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate by covering the purpose and output attributes. However, it lacks completeness for operational use in AWS ECS, such as mentioning region scoping, permission needs, or how to handle large result sets, which are common in cloud list operations.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately avoids discussing parameters, focusing instead on the tool's output semantics, which is efficient and adds value beyond 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 ('Lists') and resource ('ECS clusters') with specific attributes ('status and running task counts'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_ecs_services' or 'list_eks_clusters', which would require mentioning ECS-specific clustering versus services or EKS clusters.
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 'list_ecs_services' for service-level details or 'list_eks_clusters' for Kubernetes clusters. The description lacks context about prerequisites, permissions, or typical use cases, 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 it 'lists' users, implying a read-only operation, but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, or output format. For a 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.
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 action and resource, making it easy to parse quickly, which is ideal for a simple 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?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. However, it lacks context on output (e.g., what data is returned) and behavioral details, which could be helpful for an agent. It meets basic needs 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.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate, earning a baseline score of 4 since it doesn't need to compensate for any schema 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 verb ('Lists') and resource ('IAM users in the AWS account'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_users_without_mfa' or other user-related tools, which would require more specificity 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 prerequisites (e.g., AWS permissions), context (e.g., for auditing or troubleshooting), or how it differs from other list tools in the sibling set, 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?
No annotations are provided, so the description carries full burden. It mentions what data is returned (runtimes and last modified dates) but doesn't disclose behavioral traits like pagination, rate limits, authentication requirements, error handling, or whether it lists all functions or applies any filters. For a read operation 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 that front-loads the core action and includes relevant details. There's no wasted verbiage or redundancy, 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, no annotations, and no output schema, the description provides basic purpose but lacks completeness. It doesn't cover behavioral aspects, output format details, or usage context, which are important for an agent to use it effectively in a server with many sibling tools.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the output content. This meets the baseline for tools with no 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 ('Lists') and resource ('Lambda functions'), specifying what information is included ('with runtimes and last modified dates'). It distinguishes from generic list tools by specifying the AWS Lambda context, though it doesn't explicitly differentiate from potential similar list tools in the sibling set.
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, or any sibling tools that might be relevant for related queries. It's a standalone statement 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool lists instances with engine versions and status, but does not cover critical aspects like authentication requirements, rate limits, pagination behavior, error handling, or whether it's a read-only operation. For a tool with zero 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence: 'Lists RDS instances with engine versions and status.' It is front-loaded with the core action and resource, with no wasted words or redundant information, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (simple listing with no parameters) and the lack of annotations and output schema, the description is minimally adequate. It states what the tool does but lacks details on behavior, output format, or usage context. For a no-parameter tool, it meets basic needs but could be more complete by addressing behavioral aspects.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter semantics, but this is appropriate given the lack of parameters. The baseline score is 4 because the schema fully covers the parameters (none), and the description does not need to compensate.
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 'Lists RDS instances with engine versions and status,' which is a specific verb ('Lists') and resource ('RDS instances') with additional details ('engine versions and status'). It distinguishes from siblings like 'list_ec2_instances' by specifying RDS, but does not explicitly differentiate from other AWS listing tools 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?
The description provides no guidance on when to use this tool versus alternatives, such as other AWS listing tools in the sibling list (e.g., 'list_ec2_instances' or 'list_dynamodb_tables'). It lacks context on prerequisites, exclusions, or specific scenarios for usage, leaving the agent to infer based on the resource 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 but only states it lists secrets (names only). It doesn't disclose behavioral traits like pagination, rate limits, authentication needs, error conditions, or what 'names only' entails (e.g., no metadata). This leaves significant gaps in understanding how the tool behaves.
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 directly states the tool's function and scope. It's front-loaded and appropriately sized for a simple list operation, 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 low complexity (0 params, no output schema) and lack of annotations, the description is minimally adequate but incomplete. It covers the basic purpose but misses behavioral details like output format or constraints, which could be important for a list operation in a security context like Secrets Manager.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add param info, which is appropriate here, and the baseline for 0 params is 4, as it doesn't need to compensate for any schema 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 verb ('Lists') and resource ('Secrets Manager secrets') with a specific scope ('names only'), making the purpose unambiguous. It doesn't distinguish from siblings since there are no other secret-related tools in the list, but it's sufficiently specific for its 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 or in what context. The description only states what it does, without mentioning prerequisites, limitations, or comparison to other tools, leaving usage decisions entirely to the 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the output format ('names only'), which is helpful, but lacks critical details such as whether this is a read-only operation, pagination behavior, rate limits, authentication requirements, or error conditions. For a 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.
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 purpose and includes a clarifying detail ('names only') that adds value without verbosity.
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, no output schema, no annotations), the description is minimally adequate. It specifies the output scope ('names only'), which is useful, but lacks details on behavioral aspects like pagination or error handling. For a list operation with no structured support, it could be more 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 tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the input (none required). The description doesn't need to add parameter information, and it appropriately doesn't mention any. A baseline of 4 is applied since no parameters exist, and the description doesn't introduce confusion.
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 ('Lists') and resource ('SSM Parameters'), and specifies the scope ('names only'), which provides a specific verb+resource+scope combination. However, it doesn't explicitly differentiate from potential sibling tools (though none appear to be SSM-related in the provided list), so it falls short of 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 context. It simply states what the tool does without indicating appropriate scenarios or limitations.
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 ('Lists') but doesn't describe key behaviors such as whether it requires specific IAM permissions, if it's read-only (implied but not stated), how results are formatted (e.g., JSON list), or any rate limits or pagination. This leaves significant gaps for an agent 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 that front-loads the key information ('Lists Elastic IPs...') with no wasted words. It's appropriately sized for a simple list operation with no parameters, 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's low complexity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on usage, behavioral traits, or output format. For a simple read operation, this might suffice, but it doesn't provide enough guidance for optimal agent use without additional assumptions.
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, so it appropriately avoids redundancy. A baseline of 4 is applied since no parameters exist, and the description 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 ('Lists') and resource ('Elastic IPs that are not associated with any instance'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_ec2_instances' or 'list_internet_gateways', which would require mentioning it's specifically for unassociated EIPs versus other AWS 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 AWS permissions), typical use cases (e.g., cost optimization or security audits), or how it relates to siblings like 'list_ec2_instances' for broader instance management.
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 lists volumes, but doesn't disclose behavioral traits such as whether it requires authentication, rate limits, pagination, error handling, or the format of returned data. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.
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 front-loads the key information ('Lists EBS volumes') and adds a clarifying condition ('that are available'). There is no wasted text, 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 no parameters and no output schema, the description is minimally adequate. It explains what the tool does but lacks context on authentication, data format, or error handling. For a simple list operation, this might suffice, but without annotations, it leaves the agent to guess about behavioral aspects.
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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, focusing instead on the tool's purpose. This meets the baseline for tools with no 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 ('Lists') and resource ('EBS volumes'), specifying they must be 'available (not attached to any instance)'. It distinguishes from siblings like 'list_ec2_instances' by focusing on unused volumes, though it doesn't explicitly differentiate from other volume-related tools (none exist in the sibling 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. The description implies it's for finding unattached volumes, but it doesn't mention prerequisites (e.g., AWS permissions), typical use cases (e.g., cost optimization), or what to do with the results. Without annotations or context, the agent must 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?
With no annotations provided, the description carries full burden but only states the basic action without disclosing behavioral traits like pagination, rate limits, permissions required, or output format. It mentions regional scope, which adds some context, but overall transparency is limited.
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, clearly front-loading the core action and scope. It's appropriately sized for a simple listing 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, no output schema, no annotations), the description is adequate but lacks depth. It covers the basic purpose and scope but misses details like output structure, error handling, or integration with siblings, leaving gaps 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?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, aligning with the minimal requirement for such cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lists') and resource ('all VPCs') with regional scope ('in the current region'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'list_subnets' or 'list_security_groups' beyond the resource type, missing explicit sibling 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. The description lacks context about prerequisites, alternatives for filtered listings, or regional constraints beyond the implicit scope, 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 mentions the breakdown behavior but fails to disclose critical details: whether this is a read-only operation, if it requires specific permissions, rate limits, or what the output format looks like (e.g., structured data vs. raw). For a cost analysis tool with no annotations, 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero waste: the first states the purpose, the second explains the conditional breakdown logic. It's front-loaded and appropriately sized for the tool's complexity.
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 no annotations and no output schema, the description is incomplete for a cost analysis tool. It covers the basic purpose and parameter logic but misses behavioral context (e.g., safety, permissions) and output details. However, it's adequate for a simple read operation with well-documented parameters, leaving 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?
Schema description coverage is 100%, so the schema already documents all three parameters thoroughly. The description adds marginal value by explaining the conditional effect of service_name on the breakdown logic, but doesn't provide additional syntax or format details beyond what the schema specifies. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Detailed cost analysis' and specifies the breakdown logic (by Usage Type if service_name provided, otherwise by Service). It distinguishes from siblings like get_cost_by_service by offering more granular analysis, though it doesn't explicitly name alternatives.
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 when to use it through conditional logic (service_name vs. no service_name), suggesting it's for detailed breakdowns. However, it lacks explicit guidance on when to choose this over similar tools like get_cost_by_service or get_recent_cost, and doesn't mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool returns identity information for verification but lacks details on behavioral traits such as rate limits, authentication requirements, error handling, or response format. This is a significant gap for a 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 a single, efficient sentence that front-loads the purpose without unnecessary details. Every word contributes to understanding the tool's function, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is adequate but incomplete. It explains the purpose but lacks behavioral context like response format or error conditions, which is important for a tool with no structured data to compensate.
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 documentation is needed. The description doesn't add param info, which is appropriate, earning a baseline score of 4 for this dimension.
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 ('Returns') and resource ('AWS IAM caller identity'), specifying it's used to verify credentials. It distinguishes from siblings by focusing on identity verification rather than resource listing or monitoring, though it doesn't explicitly name alternatives.
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 credential verification, providing some context. However, it doesn't explicitly state when to use this tool versus alternatives like checking IAM users or roles directly, nor does it mention prerequisites like required AWS 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 the tool lists users, implying a read-only operation, but does not disclose behavioral traits such as permissions required, rate limits, pagination, or output format. This leaves significant gaps for a tool that likely interacts with IAM.
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 front-loads the key information without any wasted words. It directly states the tool's purpose, making it highly concise and well-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?
Given no annotations, no output schema, and the tool's potential complexity in IAM operations, the description is incomplete. It lacks details on behavioral aspects like authentication needs, error handling, or result format, which are crucial for effective use in a security 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 has 0 parameters with 100% coverage, so no parameters need documentation. The description does not add parameter details, which is acceptable given the schema completeness, aligning with the baseline for zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Lists') and resource ('IAM users') with a specific filter condition ('who do not have MFA enabled'). It distinguishes from the sibling tool 'list_iam_users' by specifying the MFA filter, making the purpose specific and differentiated.
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 identifying IAM users without MFA, but does not explicitly state when to use this tool versus alternatives like 'list_iam_users' or other security-related tools. It provides context but lacks explicit guidance on 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?
With no annotations provided, the description carries full burden but only states the filtering behavior. It doesn't disclose whether this is a read-only operation, what permissions are required, whether it's resource-intensive, what format the output takes, or any rate limits. For a security auditing 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 front-loads the core purpose and includes essential details (filtering criteria and defaults) without any wasted words. Every element serves a clear purpose, 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?
For a single-parameter tool with 100% schema coverage but no annotations or output schema, the description adequately covers purpose and parameter context. However, as a security tool with potential operational implications, it should ideally mention permission requirements or output format to be fully complete. It's minimally viable but has 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?
Schema description coverage is 100%, so the schema already documents the 'ports' parameter completely. The description adds value by explaining the default values (22, 3389) and the security context (checking for overly permissive ingress), providing semantic meaning beyond the schema's technical specification. With only one parameter, this is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Lists security groups') with precise filtering criteria ('that allow ingress from 0.0.0.0/0 on specified ports'), distinguishing it from the generic 'list_security_groups' sibling tool by specifying a security-focused subset. It uses a specific verb+resource+scope pattern that leaves no ambiguity about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the filtering criteria (security groups with overly permissive rules), suggesting it's for security auditing. However, it doesn't explicitly state when to use this vs. the generic 'list_security_groups' tool or other security tools, nor does it provide exclusion criteria or prerequisites. The guidance is contextual but not explicit.
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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