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 and does so effectively. It reveals performance characteristics ('FAST: 15-30sec vs 40-60sec'), output structure ('Returns structured health data'), and specific behavioral guidance about deployment slots. It also mentions the return format and what data to expect, though it could provide more detail about error handling or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with front-loaded key information, uses emoji for visual emphasis, and every sentence adds value. It's appropriately sized for a complex tool with 13 parameters, providing essential information without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 13 parameters, no annotations, and no output schema, the description does a good job covering the essentials: purpose, usage scenarios, key parameters, and return format. However, given the complexity and lack of structured output documentation, it could benefit from more detail about the exact structure of returned health data or error conditions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context beyond the 69% schema coverage by explaining the purpose of key parameters ('Required: environment. Optional: minutesBack (default 60), logType (http/application/all), slot') and providing practical guidance about when to use them. It clarifies the slot parameter's purpose and mentions the default for minutesBack, though it doesn't cover all 13 parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('stream and analyze logs directly without downloading') and distinguishes it from download-based alternatives by highlighting speed advantages. It identifies the resource (logs) and the key benefit (fast streaming analysis vs. download+analyze).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage contexts ('deployment verification, health checks, or real-time diagnostics') and includes specific guidance about when to use certain parameters ('Set slot=true when analyzing deployment slots'). However, it doesn't explicitly contrast this tool with sibling alternatives like 'download_logs' or 'discover_logs', which would be needed for a perfect score.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behaviors: execution time ('ANALYSIS: <5s'), input requirements ('Takes output from two analyze_logs_streaming() calls'), return values ('Returns safety recommendation... with detailed reasoning'), and decision criteria ('based on error rate changes, performance degradation, and health score delta'). It doesn't mention error handling or rate limits, but covers most essential behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by key behavioral details. Some sentences could be more concise (e.g., 'Required: baseline, slot objects' is redundant with schema), but overall it's efficient with zero wasted sentences. The emoji and formatting (ANALYSIS, Returns) enhance readability without adding bulk.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters with nested objects, no output schema, no annotations), the description does well to explain the workflow, input sources, decision logic, and return format. It covers the essential context needed to use the tool correctly in the deployment workflow. The main gap is the lack of output schema, but the description compensates by detailing what the tool returns (decision and supporting metrics).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal parameter semantics beyond the schema: it clarifies that baseline and slot objects come from analyze_logs_streaming calls and that they're required. It mentions the thresholds parameter indirectly through 'error rate changes, performance degradation, and health score delta' but doesn't add syntax or format details beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: compare baseline vs slot logs to make deployment decisions. It specifies the verb 'compare' and resources 'baseline vs slot logs', distinguishing it from sibling tools like analyze_logs_streaming (which provides input) and complete_deployment/reset_deployment (which execute decisions). The description explicitly mentions it returns a safety recommendation with reasoning.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Use in deployment workflow: analyze baseline → deploy → analyze slot → compare → decide to complete or reset.' It names the required sibling tool (analyze_logs_streaming) and specifies when to use this tool (after analyzing both baseline and slot logs). It also indicates the tool's role in the decision-making process (proceed/investigate/abort).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does an excellent job disclosing behavioral traits: it specifies async timing (2-15min), state transitions, monitoring behavior, event emission, and environment-specific differences. It doesn't mention error handling or auth requirements, keeping it from a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with front-loaded key information (purpose, timing, methods), uses clear sections with bullet-like formatting, and every sentence adds value without redundancy. It balances detail with brevity for a complex tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex deployment tool with no annotations, no output schema, and 6 parameters, the description provides strong context about behavior, timing, and usage. It falls short of perfect because it doesn't explain return values or error cases, and leaves some parameters undocumented.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 6 parameters, the description compensates well by explaining the purpose of 'deploymentId' (required) and 'monitor' (optional with default behavior). However, it doesn't mention 'projectName', 'projectId', 'apiKey', or 'apiSecret', leaving 4 parameters undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Finalize deployment after verification') and distinguishes it from siblings like 'start_deployment' and 'reset_deployment' by focusing on completion. It explicitly mentions the resource (deployment) and the action (finalize/completion).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('after verification'), preferred methods (subscribe to resource vs. monitor fallback), and distinguishes it from alternatives by describing deployment state transitions. It also mentions prerequisites ('Required: deploymentId') and context for different environments.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 and does so effectively. It reveals the operation is ASYNC (30-90min), describes content flow direction ('CONTENT typically flows downward'), warns it's a 'heavy operation', specifies required parameters, and explains the return value ('Returns operation ID for tracking'). It doesn't cover all possible edge cases like error handling, but provides substantial behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core purpose and key behavioral traits. Every sentence adds value: the first states the purpose and timing, the second provides usage context, the third explains parameter semantics, the fourth gives flow direction and warnings, and the fifth covers requirements and monitoring. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex async operation with 6 parameters, no annotations, and no output schema, the description is largely complete. It covers purpose, timing, usage scenarios, parameter guidance, operational warnings, and monitoring instructions. The main gap is lack of explicit error handling or rollback information, but given the context, it provides sufficient guidance for effective tool use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 6 parameters, the description compensates well by explaining the semantics of key parameters: it clarifies that 'includeBlob=true' copies static files/media and is slower, 'includeDB=true' copies CMS/Commerce databases, and 'sourceEnvironment' and 'targetEnvironment' are required. It doesn't explain 'projectName', 'projectId', 'apiKey', or 'apiSecret', but provides meaningful context for the most critical parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('copy database and/or blob content between environments') and distinguishes it from siblings by focusing on environment-to-environment content copying, which is unique among the listed tools that primarily handle logs, deployments, monitoring, and downloads.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use the tool ('Use for refreshing staging/test environments with production data or promoting content changes') and includes important exclusions/warnings ('This is a heavy operation - verify target environment before starting'). It also references an alternative tool ('Use status() tool to monitor progress'), making usage context comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key traits: it's a read-only operation (implied by 'Show'), returns specific data (name, ID, environment access), has performance characteristics ('INSTANT: <1s'), and has no side effects. However, it doesn't mention error cases or authentication requirements, leaving minor gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: it starts with the core purpose, includes performance and return details, provides usage guidance, and ends with parameter info—all in four efficient sentences with no redundant information. Every sentence adds value, making it front-loaded and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is nearly complete: it covers purpose, usage, behavior, and returns. However, without an output schema, it could benefit from more detail on the return format (e.g., structure of 'active project info'), though the listed fields (name, ID, environment access) mitigate this. It's adequate but has a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so the baseline is 4. The description reinforces this by explicitly stating 'No parameters', which adds clarity and prevents confusion. No additional parameter details are needed, making this sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Show currently active project context') and resource ('project'), distinguishing it from siblings like 'get_project' or 'list_projects' by focusing on the active/current context rather than general project retrieval. It explicitly defines what information is returned (name, ID, environment access), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('Use to confirm project context before critical operations'), which directly informs the agent about its role in workflows. It distinguishes it from alternatives by emphasizing the 'active' context, and the 'No parameters' note helps avoid misuse. This is comprehensive usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 and excels at this. It clearly describes the async nature (10-60min duration), monitoring behavior (polls every 30s), auto-download capability, return value (exportId), and the complete workflow. This provides comprehensive behavioral context beyond what parameters alone would indicate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with emoji, clear sections, and front-loaded critical information. Every sentence adds value: async timing, monitoring behavior, return value, requirements, and workflow. It could be slightly more concise by combining some workflow details, but overall it's well-organized and information-dense.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 17 parameters, no annotations, and no output schema, the description provides excellent contextual completeness. It covers the async nature, timing estimates, monitoring behavior, return value, required parameters, database options, companion tools, and the complete agent workflow. This gives the agent sufficient understanding despite the parameter complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the baseline is 3, but the description adds meaningful context about key parameters: it explains the purpose of autoMonitor and autoDownload parameters, clarifies the required environment and database parameters, and provides workflow context that helps understand parameter interactions. However, it doesn't cover all 17 parameters individually.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Start database export') with the target resource ('from specified environment'), distinguishing it from sibling tools like db_export_status and db_export_download. It explicitly mentions the required parameters (environment, database) and the async nature of the operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool vs alternatives: it names the companion tool db_export_status() for checking progress and outlines the complete agent workflow (start export → monitor status → download). It also specifies required parameters and database options.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden and does well: it discloses that the tool returns immediately with a download ID while downloads continue in background, notes performance characteristics (large files take 5-20min), and explains the asynchronous nature. It could improve by mentioning error handling or authentication needs.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by useful context and usage notes in a logical flow. It's slightly verbose with emoji and capitalization, but every sentence adds value (e.g., background processing, monitoring guidance, parameter highlights), making it efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 12 parameters, no annotations, and no output schema, the description is fairly complete: it explains the tool's purpose, behavior, usage with siblings, and key parameters. It could be more comprehensive by covering all parameters or error cases, but it provides enough context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema: it highlights 'downloadUrl' as required and 'downloadPath' and 'background' as optional with a default, but doesn't explain other parameters like 'skipConfirmation' or credential parameters, leaving the schema to do most work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Download completed database export to local storage') with the resource ('database export') and distinguishes from siblings like 'download_status' by specifying it initiates downloads while siblings monitor them. The verb 'download' is precise and the scope is well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided: use this tool to download exports, with background processing noted, and use 'download_status()' to monitor progress. It distinguishes from alternatives by specifying this tool starts downloads while others track them, and mentions prerequisites like 'downloadUrl'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well disclosing behavioral traits: 'REAL-TIME: <1s' (performance), 'polls every 30s until complete' (monitoring behavior), 'Tool waits synchronously' (blocking behavior), and automatic download capabilities. It doesn't mention rate limits, authentication needs, or error handling, but covers most operational aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. Every sentence adds value: first states purpose and performance, second explains returns, third covers monitoring/auto-download, fourth specifies requirements, fifth explains alternative tool usage. Minor redundancy exists ('Returns status and download URL when ready' repeats earlier information).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 18 parameters and no output schema, the description does well covering operational context: purpose, performance, return values, monitoring behavior, prerequisites, and alternative tool reference. It doesn't explain the relationship between parameters (like how latest interacts with exportId) or error scenarios, but provides sufficient guidance for basic usage given the comprehensive schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 18 parameters thoroughly. The description adds minimal parameter semantics beyond the schema - it mentions 'exportId, environment' as required and explains monitor/autoDownload behaviors, but doesn't provide additional context about parameter interactions or usage patterns that aren't already in the schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs and resources: 'Check database export progress' (verb+resource), 'Returns progress percentage, estimated time remaining, and download URL when export completes' (output details), and distinguishes from sibling db_export_download by explicitly mentioning it. It goes beyond the name/title to explain what the tool actually does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool vs alternatives: 'Use db_export_download() with the URL to retrieve file' specifies the alternative tool for downloading. It also indicates prerequisites: 'Required: exportId, environment' and context for monitoring/auto-download features. This gives clear operational context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Tool has no description.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Tool has no description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool has no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Tool has no description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Tool has no description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Tool has no description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does so effectively. It discloses key behavioral traits: the operation is 'INSTANT: <1s', it 'Stops collecting tool usage analytics and error data', and 'Change persists for session'. However, it lacks details on potential side effects or error handling, leaving minor gaps in full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: it uses an emoji for quick visual cue, leads with the core action, includes performance metrics ('INSTANT: <1s'), explains the effect and optionality, notes persistence, and states parameter and return details—all in three efficient sentences with zero wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is nearly complete. It covers purpose, usage, behavior, and confirms no parameters. However, without an output schema, it only briefly mentions 'Returns confirmation of disabled telemetry' without detailing the format, leaving a minor gap in full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so the baseline is 4. The description reinforces this with 'No parameters', adding clarity that no inputs are needed, which is helpful for an agent to understand it's a simple command without configuration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Disable anonymous usage telemetry collection') and resource ('telemetry'), with the emoji reinforcing the action. It explicitly distinguishes from its sibling 'enable_telemetry' by describing the opposite function, making the purpose unambiguous and distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool: 'Telemetry helps improve MCP server but is fully optional' indicates it's for users who want to opt out of analytics. It directly contrasts with 'enable_telemetry' as the alternative, and 'Change persists for session' clarifies the temporal scope, offering clear context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 provides useful context about performance ('REAL-TIME: <2s'), return format ('Returns container names, log types available, and environment availability'), and optional parameters ('Optional: project'). However, it doesn't cover authentication requirements (despite apiKey/apiSecret parameters), rate limits, or error conditions. The description adds value but doesn't fully compensate for the lack of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with key information front-loaded (purpose, performance, returns). Every sentence adds value, though the final sentence ('Returns container inventory') is somewhat redundant with earlier information. The emoji adds visual distinction but doesn't detract from the content's efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (discovery operation with 4 parameters), no annotations, and no output schema, the description provides good purpose and usage context but has significant gaps. It doesn't explain authentication requirements despite apiKey/apiSecret parameters, doesn't detail the return structure beyond high-level categories, and provides minimal parameter guidance. The description is adequate but incomplete for a tool with authentication parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 4 parameters, the description only mentions one parameter ('Optional: project') without specifying whether this refers to projectName or projectId. It provides no information about apiKey or apiSecret parameters. The description adds minimal semantic value beyond what the bare schema provides, failing to compensate for the complete lack of parameter documentation in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('discover available log containers') and resources ('across all environments'), and distinguishes it from siblings by explicitly mentioning it should be used before download_logs() or analyze_logs_streaming(). It explains what information is returned (container names, log types, environment availability) and why it's useful (for multi-environment projects).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('Use this before download_logs() or analyze_logs_streaming() to understand what logs exist') and why ('Useful for multi-environment projects to find which environments have logging enabled'). It clearly positions this as a discovery/preparation step before other log-related operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 does an excellent job describing key behavioral traits: the async/background nature (returns immediately with download ID), the need for monitoring via another tool, and the date filtering capability. It doesn't mention rate limits, authentication requirements, or error handling, which keeps it from a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly structured and concise. It starts with the core purpose, immediately highlights the critical async behavior, then provides usage guidance, parameter context, and return values - all in 4 sentences with zero wasted words. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 14 parameters, no annotations, and no output schema, the description does remarkably well. It covers the essential behavior, usage patterns, and key parameters. The main gap is that with 14 parameters, it only explicitly mentions 4 of them, leaving many schema parameters undocumented in the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context beyond the schema's 64% coverage. It explicitly identifies 'container' and 'environment' as required parameters (though schema shows 0 required), mentions 'downloadPath' and 'dateFilter' as optional, and explains the return values (downloadId and estimated file count/size). This compensates well for the schema's incomplete coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verb ('Download') and resource ('files from Azure blob storage container to local path'). It distinguishes from sibling tools like 'download_logs' or 'download_status' by focusing on blob storage files rather than logs or status monitoring.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: it specifies when to use this tool (for downloading files from blob storage), when to use alternatives (use 'download_status()' to monitor progress), and mentions prerequisites (container and environment are required). It also distinguishes this from blocking downloads by highlighting the async/background nature.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 discloses key behavioral traits: immediate cancellation (<1s), returns count of successfully cancelled downloads, and notes a limitation (database downloads cannot be cancelled). However, it lacks details on error handling or permissions, which could be useful for a destructive operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the main action ('Cancel active download(s) immediately'), followed by key details in a logical order: timing, parameter usage, limitations, return value, and verification method. Every sentence adds necessary information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description does well by covering purpose, usage, behavior, and parameters. It could improve by specifying error cases or auth requirements, but it's largely complete for a tool with one optional parameter and clear operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the downloadId parameter. The description adds value by explaining the optional nature (omit to cancel all) and linking it to the return value (cancelled count), but doesn't provide additional syntax or format details beyond what the schema implies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'cancel' and resource 'active download(s)', specifying immediate action. It distinguishes from sibling tools like download_list (for verification) and download_status (for status checking), 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided: call with downloadId for specific cancellation or without parameters for all active downloads, and notes that database downloads cannot be cancelled due to Azure streaming limitation. It also references download_list() for verification, clearly indicating when and how to use this tool versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it specifies real-time performance ('REAL-TIME: <1s'), describes the return format in detail, mentions pagination for large histories, and notes all parameters are optional. It lacks explicit rate limit or error handling details, but covers most essential aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose and key features (filtering, pagination, real-time). Every sentence adds value, though it could be slightly more streamlined by avoiding repetition of filter details already in the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description does a good job of covering the tool's behavior, return values, and usage context. It explains what the tool returns and how to use the results with other tools, making it largely complete for a listing tool with optional parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by briefly mentioning filtering and pagination use cases, but doesn't provide additional syntax or format details. 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.

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 specific verbs ('List downloads') and resources ('download IDs, status, progress percentage, file info, and start/completion times'), distinguishing it from siblings like download_status() or download_cancel() which operate on individual downloads rather than listing them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('to find downloadId for download_status() or download_cancel() calls') and provides context for filtering by status ('to monitor ongoing downloads or review history') and type ('to track specific operations'), offering clear guidance on its application versus alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing key behaviors: asynchronous operation ('returns immediately, download continues in background'), return value ('Returns downloadId'), and monitoring requirement. It could improve by mentioning potential side effects like storage consumption or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with emoji and clear sections, but slightly verbose with background details and sibling comparison. Every sentence adds value, but could be more streamlined. The information is front-loaded with core purpose first.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Good for a complex tool with 27 parameters and no output schema. Covers purpose, usage guidelines, behavioral aspects, and references monitoring. Could be more complete by explaining output format or error conditions, but does well given the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 78% (high), so baseline is 3. The description adds some value by explaining date filtering options and log type values, but doesn't significantly enhance understanding beyond what's already documented in the comprehensive schema descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Download application logs') and resource ('from environment to local storage'), distinguishing it from siblings like analyze_logs_streaming (online analysis) and download_status (monitoring). It provides concrete purpose beyond just the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use ('when you need logs for offline analysis') and when not to use ('For quick online analysis, use analyze_logs_streaming() instead'). It also mentions prerequisites ('Required: environment') and follow-up actions ('Returns downloadId for monitoring with download_status()').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well: it discloses performance ('REAL-TIME: <1s'), polling behavior ('Poll this every 5-10s'), completion criteria ('Download completes when status="completed"'), and return format ('Returns progress, speed, ETA, file path'). It doesn't mention error conditions or rate limits, keeping it from a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: first sentence states purpose, second provides performance and return details, third gives usage frequency, fourth defines completion criteria, fifth lists requirements and returns. Every sentence adds value with zero waste, and key information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a status-checking tool with no annotations and no output schema, the description is quite complete: it covers purpose, usage, behavior, parameters, and return values. It lacks explicit error handling details and doesn't fully document the monitor parameter's output format, but otherwise provides sufficient context for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds value by explaining the downloadId parameter's purpose ('to check') and source ('from download_list'), and implicitly clarifies the monitor parameter's behavior by contrasting manual polling ('Poll this every 5-10s') with auto-monitoring. However, it doesn't fully detail the monitor parameter's combined report output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Get real-time status of specific download') and resource ('download'), distinguishing it from sibling tools like download_list (lists downloads), download_cancel (cancels downloads), and download_blobs (downloads content). It explicitly mentions what information is returned (progress percentage, speed, ETA, file path).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Poll this every 5-10s to track long-running downloads' tells when to use it, 'Download completes when status="completed" and file path is provided' tells when to stop using it, and 'Required: downloadId' indicates prerequisites. It also distinguishes from the monitor parameter's auto-polling functionality.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does an excellent job disclosing key behavioral traits: performance ('INSTANT: <1s'), data privacy ('No personal data collected, only tool names and error types'), persistence ('Change persists for session'), and confirmation behavior ('Returns confirmation of enabled telemetry'). It doesn't mention rate limits or auth needs, but covers most important aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly front-loaded with the core purpose first, followed by key behavioral details in a logical sequence. Every sentence earns its place by providing essential information without redundancy. The emoji adds visual distinction without compromising clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no annotations and no output schema, the description provides excellent coverage of purpose, behavior, and usage context. It explains what happens when invoked, what data is collected, persistence, and return value. The only minor gap is not explicitly stating whether this requires specific permissions or authentication.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0 parameters and 100% schema coverage, the baseline is 4. The description explicitly states 'No parameters' and explains what the tool does without requiring parameter input, which adds appropriate context beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Enable anonymous usage telemetry collection') and resource ('telemetry'), distinguishing it from its sibling 'disable_telemetry'. It provides concrete details about what gets enabled (tool usage patterns and error data) rather than just restating the tool name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('Resumes collecting... for product improvement') and provides clear alternatives by naming its sibling 'disable_telemetry'. It also specifies the persistence ('Change persists for session'), giving clear context for when the effect applies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively communicates key behavioral traits: performance ('INSTANT: <1s'), default behavior ('Default: 24 hour expiration, read-only'), parameter effects ('Set writable=true for write access'), and the expiration mechanism ('URL expires after specified retention period'). It doesn't mention authentication requirements or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with front-loaded essential information, using emoji for visual cue, performance indicator, and clear bullet-like statements. Every sentence adds value with no redundancy, making it easy to scan while remaining comprehensive.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (8 parameters, no annotations, no output schema), the description provides substantial context about what the tool does, when to use it, and key behavioral aspects. It explains the return value ('Returns SAS URL string') and expiration behavior. The main gap is incomplete parameter coverage, but overall it's quite helpful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 8 parameters, the description compensates well by explaining the purpose and effects of key parameters: it clarifies that 'retentionHours' controls custom expiration (1-168 hours), 'writable=true' enables write access, and that 'container' and 'environment' are required. However, it doesn't cover all 8 parameters (missing projectName, projectId, apiKey, apiSecret, and permissions enum details).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Generate temporary Shared Access Signature URL') and resource ('for storage container'), distinguishing it from sibling tools like 'list_storage_containers' or 'download_blobs'. It precisely defines the tool's function as creating time-limited access URLs for Azure Storage.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use this tool ('Use for external tools, scripts, or direct blob access'), but doesn't explicitly state when NOT to use it or mention alternatives. It doesn't differentiate from potential sibling tools that might handle similar storage access scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behaviors: it performs analysis ('ANALYSIS: <1s'), returns recommendations ('suggests which MCP tool to use with recommended parameters'), and specifies the output format ('Returns recommended tool name, suggested parameters, and reasoning'). However, it doesn't mention potential limitations like accuracy or fallback options.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by key details in a structured format (ANALYSIS, Use case, Returns, Required). Every sentence earns its place, with no wasted words, making it highly efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (AI-powered guidance with no output schema), the description is mostly complete: it explains purpose, usage, behavior, and parameters. However, without an output schema, it could benefit from more detail on the return structure (e.g., format of 'recommended parameters'), but the mention of 'reasoning' adds some context. Annotations are absent, so the description adequately compensates.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single parameter 'topic' with its description. The description adds some value by specifying 'Required: taskDescription (natural language)', which clarifies the expected input format, but this partially overlaps with the schema's 'topic' description. Since schema coverage is high, baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get AI-powered tool recommendations for natural language tasks.' It specifies the verb ('Get AI-powered tool recommendations'), resource ('natural language tasks'), and distinguishes itself from siblings by focusing on guidance rather than direct execution of tasks like deployment or monitoring.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use when uncertain which tool fits your workflow.' It also distinguishes it from alternatives by implying it's for guidance rather than direct action, which is clear given the sibling tools are all operational tools (e.g., 'analyze_logs_streaming', 'complete_deployment').

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behavioral traits: the real-time performance characteristic (<1s), the operation-specific nature of the cache, what information is returned (cache hit/miss rates by operation type), and that it's a read-only operation (implied by 'View' and 'Shows'). It doesn't mention authentication requirements or rate limits, but covers the core behavior well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. Every sentence adds value: the first states what it does, the second gives performance characteristics and architectural context, the third specifies what it shows, the fourth provides usage guidance, and the fifth clarifies parameters and returns. Minor redundancy could be trimmed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the contradiction between 'No parameters' in the description and 3 parameters in the schema, the description is incomplete and misleading. While it covers the tool's purpose and behavior adequately for a no-parameter tool, it fails to address the actual parameter requirements. With no output schema and incomplete parameter information, significant gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description explicitly states 'No parameters' while the input schema shows 3 parameters (projectName, projectId, action with enum). This is a direct contradiction. The description provides no information about any parameters, failing to compensate for the 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('View cache performance metrics', 'Shows cache hit/miss rates') and resources ('cache performance metrics', 'cache statistics by operation type'). It distinguishes itself from potential siblings by emphasizing 'operation-specific (no central management)' and focusing on performance metrics rather than management functions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool ('Use to understand caching effectiveness') and mentions its real-time nature ('REAL-TIME: <1s'). However, it doesn't explicitly state when NOT to use it or name specific alternative tools among the siblings for different cache-related needs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well: it discloses performance ('REAL-TIME: <2s'), polling behavior ('poll every 30s until reaches AwaitingVerification'), and workflow dependencies. It doesn't mention rate limits, authentication needs, or error handling, but provides substantial behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: first sentence states purpose, second adds performance and return details, third explains monitoring behavior, fourth covers workflow. Every sentence adds value with zero waste, and it's appropriately front-loaded with core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, no annotations, and no output schema, the description does well: it explains the deployment workflow, monitoring behavior, and key parameters. It doesn't fully document all parameters or the exact return format, but provides enough context for effective use given the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low (29%), but the description compensates by explaining key parameters: 'deploymentId' is required, 'monitor=true' enables polling, and 'waitBeforeCheck' pauses before checking. It doesn't cover 'projectName', 'projectId', 'apiKey', or 'apiSecret', but adds meaningful context for the most critical parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get detailed deployment status and progress' with specific status values (InProgress, AwaitingVerification, etc.) and what information is returned. It distinguishes from siblings like 'list_deployments' (which lists deployments) and 'complete_deployment' (which finalizes deployments).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Agent workflow: After start_deployment() → poll status until AwaitingVerification → test slot URL → complete_deployment()' and mentions when to use monitoring mode. It distinguishes this tool from 'complete_deployment' and 'reset_deployment' by explaining its role in the deployment workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively adds context beyond basic functionality: it specifies real-time performance ('REAL-TIME: <1s'), details the return values (e.g., total monitor count, active monitors), and clarifies there are no parameters. This covers key behavioral traits like speed and output format, though it could mention error handling or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded, starting with the core action and key details (real-time performance, return values). Every sentence earns its place by providing essential information without redundancy, such as clarifying the lack of parameters and usage context, making it efficient and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is largely complete: it explains the purpose, behavior, and usage. However, it could be more comprehensive by detailing the exact format of the 'monitoring statistics summary' returned, as there is no output schema to rely on, leaving some ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so the schema fully documents the absence of parameters. The description reinforces this by stating 'No parameters', adding no extra semantic value but aligning perfectly. Since there are no parameters, the baseline is 4, as the description does not need to compensate for any gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Get aggregate statistics') and resources ('for all monitors'), distinguishing it from sibling tools like 'list_monitors' (which likely lists individual monitors) or 'stop_monitoring' (which controls monitoring). It explicitly mentions what it returns, making the purpose distinct and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use this tool ('Use to understand monitoring load and system activity'), which helps differentiate it from siblings such as 'get_deployment_status' or 'health_check'. However, it does not explicitly state when not to use it or name specific alternatives, missing full comparative guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: real-time performance (<1s), specific return data fields, and that it returns a 'full project config object'. However, it doesn't mention error conditions, authentication requirements, or rate limits which would be valuable 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with key information front-loaded: purpose, performance characteristics, return data, usage context, and parameter requirement. Every sentence adds value with no redundant information. The emoji adds visual distinction without compromising clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with no annotations and no output schema, the description provides adequate coverage of purpose and basic behavior but has significant gaps. It doesn't explain the parameter semantics adequately (critical with 0% schema coverage), doesn't describe error conditions, and while it mentions return fields, doesn't provide structure details for the 'full project config object'.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 2 parameters, the description must compensate but provides minimal parameter guidance. It mentions 'Required: projectName' but doesn't explain the relationship between projectName and projectId parameters, nor clarifies if both can be used together or are alternatives. The schema shows both are optional (no required parameters), creating potential confusion.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verb ('Get') and resource ('detailed project configuration'), and distinguishes it from siblings like 'list_projects' by specifying it returns detailed configuration rather than just listing. It explicitly mentions what information is returned (project ID, name, environments, hosting type, credential status).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use the tool ('to inspect project settings or troubleshoot configuration issues'), but doesn't explicitly state when NOT to use it or name specific alternatives. While it distinguishes from 'list_projects' by implication, it doesn't explicitly compare with other sibling tools like 'current_project' or 'update_project'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key traits: real-time performance (<1s), what information is shown (requests remaining, reset times, usage percentage), and API limits (30/min, 500/hour per project). It doesn't cover error handling or authentication needs, but provides substantial 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with key information front-loaded: purpose, performance, data shown, limits, usage guidance, parameters, and returns. Every sentence adds value without 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.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only tool with no output schema, the description provides comprehensive context about what metrics are returned (rate limit metrics and reset timestamps) and operational details. It covers purpose, behavior, and usage well, though parameter semantics could be more complete given the 0% schema coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for its 2 parameters (projectName, projectId), and the description only mentions 'Optional: project' without explaining the difference between name and ID or when to use each. This adds minimal value beyond the schema, resulting in a baseline score for inadequate parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('View current API rate limit status') and resource ('Optimizely API'). It distinguishes from siblings by focusing on rate limits rather than logs, deployments, or other operations, making its scope immediately apparent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('Use before batch operations to avoid hitting limits'), providing clear context for its application. It implies alternatives by focusing on rate limit checks, though no specific sibling tools are named for comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses performance ('INSTANT: <1s'), return content (support resources object with specific elements), and clarifies it has no parameters. However, it doesn't mention authentication requirements, rate limits, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, followed by performance, return details, usage guidance, and parameter info in just three sentences. Every sentence adds value with zero waste, using emoji and formatting for readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, parameterless tool with no annotations or output schema, the description is nearly complete: it explains purpose, usage, behavior, and returns. It could improve by specifying the exact structure of the 'support resources object' or error handling, but gaps are minor given the tool's simplicity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema coverage, so baseline is 4. The description explicitly states 'No parameters,' which adds clarity beyond the empty schema, confirming this is a parameterless operation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Get support contact information and documentation') and resources (email, URLs, links, page). It distinguishes from sibling tools by focusing on support resources rather than operational functions like deployment or monitoring.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'Use when you need help or want to report issues.' This provides clear context for invocation and differentiates it from other tools that handle technical operations rather than support requests.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes performance characteristics ('REAL-TIME: <1s'), external dependencies ('Checks local version against NPM registry'), and the action triggered by results ('Suggests npm update command if outdated'). However, it doesn't mention error handling 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with an emoji visual cue, performance metric upfront, clear purpose statement, usage guidance, and output details - all in 4 concise sentences with zero redundant information. Every sentence adds essential value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool with no annotations or output schema, the description provides excellent context about what the tool does, when to use it, performance characteristics, and what information it returns. The only minor gap is lack of explicit error handling information, but overall it's quite complete for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the baseline would be 3. The description adds value by explaining that no parameters are needed because it automatically checks both local and registry versions, providing context beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific verb ('Get') and resource ('current MCP server version and update availability'), distinguishing it from sibling tools like 'health_check' or 'status' by focusing on version information rather than operational status. It explicitly mentions checking against NPM registry, which further clarifies its unique purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('to verify you have latest features and bug fixes') and provides a clear alternative action ('Suggests npm update command if outdated'), giving the agent direct guidance on usage context and next steps based on the output.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes the tool's behavior: real-time operation (1-2s), what information it returns (telemetry status, API rate limit info, etc.), and that it has no parameters. It doesn't mention authentication requirements or rate limits, but covers the core operational behavior well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with three sentences that each serve distinct purposes: stating the tool's function, specifying its behavior and return values, and providing usage guidance. There's no wasted language, and the information is front-loaded appropriately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter health check tool with no output schema, the description provides good completeness by explaining what information is returned and when to use it. The main gap is the mismatch between 'No parameters' in the description and the 5-parameter input schema, which creates some ambiguity about actual usage requirements.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description states 'No parameters' which directly addresses the parameter semantics. However, the input schema shows 5 parameters with only 20% description coverage. The description compensates by clarifying that no parameters are needed for the health check operation, though it doesn't explain why the schema includes parameters like projectId or apiKey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check MCP server overall health status' with specific components like telemetry status, API rate limit info, active background monitors count, and system resource usage. It distinguishes itself from siblings like 'test_connection' or 'get_rate_limit_status' by providing a comprehensive health overview rather than specific functionality.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use this to verify server is operating normally before critical operations.' This provides clear context for usage and distinguishes it from other monitoring tools like 'get_monitoring_stats' or 'get_cache_status' which serve different purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 does an excellent job: it discloses performance characteristics ('REAL-TIME: <2s'), return format ('Returns deployment IDs, status...'), and practical usage guidance. The only minor gap is it doesn't mention authentication requirements or rate limits, but given the comprehensive behavioral information provided, this deserves a high score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly structured and concise. It starts with the core purpose, then provides key behavioral information, parameter guidance, and alternative tool usage - all in 4 sentences with zero wasted words. Every sentence earns its place by adding value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a list/filter tool with 10 parameters and no annotations or output schema, the description provides excellent completeness. It covers purpose, performance, return format, parameter guidance, and alternative tools. Given the complexity of the tool (10 parameters, filtering capabilities), the description gives the agent everything needed to use it correctly without being overwhelming.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 40%, but the description compensates well by explaining key parameters: it clarifies that 'activeOnly=true' shows 'only in-progress/awaiting deployments' and that pagination parameters are 'for large deployment histories.' It also states 'All parameters optional' which is helpful context. While it doesn't cover all 10 parameters, it adds meaningful semantics for the most important ones beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List recent deployments with filtering and pagination.' It specifies the verb ('List'), resource ('deployments'), and scope ('recent'), and distinguishes from sibling tools by mentioning get_deployment_status() for detailed info on specific deployments. This is specific and distinguishes from alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool versus alternatives: 'Use get_deployment_status() for detailed info on specific deployment.' It also explains when to use specific parameters: 'Set activeOnly=true to show only in-progress/awaiting deployments' and 'Use pagination (limit, offset) for large deployment histories.' This gives clear context for usage decisions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key traits: it's a read operation (implied by 'List'), specifies real-time performance ('REAL-TIME: <1s'), and clarifies the return format ('Returns array of active monitor details'). However, it doesn't mention potential limitations like rate limits or authentication needs, leaving some gaps for a tool with no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is highly concise and well-structured: it starts with an emoji for visual clarity, states the purpose upfront, includes performance details, lists what it shows, provides usage guidance, notes the lack of parameters, and specifies the return type—all in three efficient sentences with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is nearly complete: it covers purpose, behavior, usage, and output. However, without annotations or an output schema, it could benefit from more detail on the exact structure of the returned array (e.g., field examples or data types) to fully guide the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so the baseline is 4. The description adds value by explicitly stating 'No parameters,' which reinforces the schema and prevents confusion, though it doesn't need to explain any parameters beyond that.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('active background monitors tracking deployments'), distinguishing it from siblings like 'list_deployments' or 'get_monitoring_stats' by specifying it shows monitor details including IDs, deployment IDs, status, and update count. It explicitly identifies the scope as real-time active monitors, not historical or aggregated data.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool: 'Use to discover active monitors for stop_monitoring() or update_monitoring_interval() calls.' It directly names alternative tools for related actions, helping the agent choose correctly based on the goal of finding monitors to stop or update.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing performance characteristics ('REAL-TIME: <1s'), return format ('Returns project names, IDs, hosting types, and active status'), and output structure ('Returns array of project summaries'). It doesn't mention pagination behavior or error conditions, keeping it from a perfect score.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely well-structured and front-loaded: starts with purpose, adds performance context, specifies return format, provides usage guidance, and notes parameter situation. Every sentence earns its place with zero wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only listing tool with no output schema, the description provides excellent context: purpose, performance, return format, usage guidance. It's missing details about pagination behavior (implied by parameters but not explained) and error cases, but otherwise quite complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents both parameters. The description states 'No parameters' which contradicts the schema showing 2 optional parameters, but since schema coverage is complete, baseline 3 is appropriate. The description doesn't add meaningful parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('all configured projects in multi-project setup'), and distinguishes from siblings by specifying it's for discovering available projects before using switch_project(). It's specific about scope and differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool ('Use to discover available projects before switch_project() call'), providing clear context and naming a specific alternative. This gives the agent perfect guidance on when this tool is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing performance characteristics ('REAL-TIME: 1-3s'), return format ('Returns container names, types, and creation dates'), and that it 'Returns array of container details.' However, it doesn't mention pagination behavior (though offset/limit are in schema) or error conditions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with key information front-loaded: emoji for visual cue, purpose statement, performance data, return format, usage guidance, and parameter requirements. Every sentence adds value with zero wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 7 parameters, no annotations, and no output schema, the description does well by covering purpose, usage, performance, and return format. However, it doesn't fully address all parameters or provide complete behavioral context for a listing operation with authentication parameters (apiKey, apiSecret).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With only 29% schema description coverage, the description compensates by explaining the purpose of 'environment' and 'project' parameters. However, it doesn't address the other 5 parameters (limit, offset, projectName, projectId, apiKey, apiSecret) that appear in the schema but aren't mentioned in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('List Azure blob storage containers'), resource ('containers'), and scope ('for environment'). It distinguishes from siblings by specifying container types (logs, blobs, websitelogs) and explicitly mentions related tools (download_blobs, generate_storage_sas_link).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('to discover available containers before download_blobs() or generate_storage_sas_link() calls') and mentions that 'Containers vary by environment and project configuration.' It also specifies required and optional parameters directly in the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: performance characteristics ('REAL-TIME: <1s'), what it returns ('only critical issues and in-progress deployments without detailed logs'), and output format ('filtered deployment summary'). It doesn't mention error handling or authentication needs, but provides substantial 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely efficient with every sentence earning its place. Front-loaded with the core purpose, followed by performance characteristics, scope limitations, usage guidance, output description, and parameter note - all in a compact format with zero wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple status-check tool with one optional parameter and no output schema, the description provides excellent context about what the tool does, when to use it, performance expectations, and output characteristics. The main gap is lack of explicit error handling information, but otherwise it's quite complete for this complexity level.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with only one optional parameter 'project' already documented in the schema. The description adds minimal value by mentioning 'Optional: project' but doesn't provide additional context beyond what the schema already states about default behavior. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a 'fast status check for active deployments only' with specific scope (critical issues and in-progress deployments without detailed logs). It distinguishes from siblings by emphasizing speed and filtering, differentiating from tools like 'get_deployment_status' or 'list_deployments' that likely provide more comprehensive information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use: 'for quick health checks before starting new operations.' This provides clear context about the intended use case and timing, helping the agent choose this over more detailed status tools when speed is prioritized over completeness.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 and does so effectively. It reveals the tool is ASYNC (5-15min), describes what gets reversed ('all changes made by deployment, restoring previous code and optionally database'), mentions the resulting status ('Deployment transitions to "Reset" status'), and provides workflow guidance. No contradictions exist since annotations are absent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. Every sentence adds value: the first states what it does, the second gives timing and scope, the third provides usage context, the fourth explains a key parameter, the fifth describes outcome, and the sixth gives workflow guidance. Minor room for improvement in flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description provides substantial context about behavior, timing, outcomes, and workflow. It covers the essential 'what happens' and 'when to use' aspects well. The main gap is incomplete parameter coverage, but otherwise it's quite comprehensive given the complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for 5 parameters, the description partially compensates by explaining the purpose of one parameter ('Set resetWithDbRollback=true to also rollback database changes') and mentioning that 'deploymentId' is required. However, it doesn't cover the other 3 parameters (projectName, projectId, apiKey, apiSecret), leaving significant gaps in parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verb ('Rollback') and resource ('deployment to previous state'), and distinguishes it from siblings by mentioning its unique rollback functionality. It goes beyond the name 'reset_deployment' by explaining what 'reset' means in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool ('when deployment verification fails or errors detected') and provides a complete agent workflow with a specific alternative tool ('investigate logs with analyze_logs_streaming()'). This gives clear guidance on both usage context and next steps.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses key behavioral traits: real-time performance (<1s), return values (path, free space, permissions), and operational checks (configuration validity, file system permissions). However, it doesn't mention error handling or edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with key information (purpose and real-time performance), followed by usage guidance and return details. Some redundancy (e.g., 'Returns' mentioned twice) slightly reduces efficiency, but overall well-structured and concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description provides good coverage: purpose, usage context, performance, return values, and parameter semantics. It could improve by detailing error conditions or output format specifics, but it's largely complete for a read-only configuration tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying that the 'projectName' parameter is optional and specifying what the tool returns (path, free space in GB, permissions), enhancing understanding beyond the schema's basic description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('show download directory configuration and disk space') and resource ('download directory'), distinguishing it from sibling tools like 'download_list' or 'download_status' by focusing on configuration and space checking rather than download operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use this tool ('before starting large downloads to ensure sufficient space') and provides context on its purpose (configuration validity and file system permissions checks), with no misleading guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behavioral traits: the async nature (5-30min), auto-monitoring with real-time updates, immediate return of deploymentId, and the different flow directions for CODE vs CONTENT deployments. It doesn't mention rate limits, authentication needs, or error handling, but covers most operational aspects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with zero wasted sentences. It front-loads the core purpose, then provides operational details, flow rules, return values, and usage guidance in a logical progression. Each sentence earns its place by adding distinct value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex deployment tool with 14 parameters, no annotations, and no output schema, the description provides substantial context about behavior, flow rules, and next steps. It explains the deployment process lifecycle and how this tool fits within it. The main gap is lack of information about authentication (apiKey, apiSecret) and some optional parameters, but overall it's quite comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With only 14% schema description coverage, the description compensates well by explaining the purpose of key parameters: it clarifies when to use includeBlob and includeDB, and specifies that sourceEnvironment and targetEnvironment are required. While it doesn't cover all 14 parameters, it adds meaningful context for the most critical ones beyond what the bare schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Start'), resource ('new deployment'), and scope ('from source to target environment'). It distinguishes this tool from siblings like 'complete_deployment' and 'get_deployment_status' by specifying it initiates the deployment process, not monitors or finalizes it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool vs alternatives: it specifies that after status reaches 'AwaitingVerification', the agent should use 'get_deployment_status()' and 'complete_deployment()' instead. It also distinguishes between CODE and CONTENT deployment flows, helping the agent choose appropriate source/target environments.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: real-time performance (<1s), return values (deployment states, progress percentage, error details, active deployment info, environment health metrics), and optional parameters. It doesn't mention rate limits or authentication needs, but covers core functionality adequately.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose in the first sentence. Every sentence adds value: real-time performance, return details, usage guidance, and parameter mention. Minor redundancy in mentioning returns could be trimmed, but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description does well to explain return values and behavioral context. It covers the tool's purpose, usage, performance, and outputs adequately for a status-checking tool. Could improve by specifying error handling or data freshness, but largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters fully. The description mentions the parameters ('Optional: environment, project') but adds no meaningful semantics beyond what the schema provides. 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.

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 specific verbs ('Show current deployment status and environment health') and resources ('deployment states', 'progress percentage', 'error details', 'environment health metrics'). It distinguishes from siblings like 'get_deployment_status' by emphasizing real-time health checking and investigation needs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('Use this to check if deployments need completion or investigation') and distinguishes it from alternatives by focusing on real-time status and health metrics rather than historical data or specific deployment details provided by siblings like 'list_deployments' or 'get_deployment_status'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behaviors: the action is instantaneous (<1s), it stops polling immediately, returns final deployment status, and removes the monitor from the active list. However, it doesn't mention potential side effects like whether this affects other monitoring processes or if the action is reversible, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with key information front-loaded: the action, speed, immediate effect, and return value. Every sentence adds value—none are redundant. The use of emoji and formatting (INSTANT: <1s) enhances readability without wasting space.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 2 parameters, 0% schema coverage, no annotations, and no output schema, the description provides good behavioral context but falls short on parameter documentation. It mentions a 'monitorId' requirement that conflicts with the schema, creating inconsistency. While it covers the tool's purpose and usage well, the parameter confusion reduces overall completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 2 parameters (deploymentId, all) with 0% description coverage, meaning the schema provides no semantic information. The description only mentions 'Required: monitorId' (which doesn't match the schema parameters), creating confusion rather than adding meaningful context. This fails to compensate for the schema's lack of documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Stop background monitoring for deployment') and resource ('deployment'), distinguishing it from siblings like 'list_monitors' or 'get_deployment_status'. It uses a precise verb ('Stop') and specifies the scope ('background monitoring'), making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool ('when deployment completes or when manual monitoring is preferred') and provides context on its effect ('Monitor is removed from active monitors list'). This gives clear guidance on appropriate scenarios, helping the agent choose between this and alternatives like 'get_deployment_status' or 'list_monitors'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden and discloses key behavioral traits: instant execution (<1s), changes default credentials and project ID for all subsequent calls, context persists for the entire session, and returns new active project details. It doesn't mention error cases or side effects, but covers most critical aspects well.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by key details (speed, effect, usage context, prerequisites, returns, and sibling reference). Every sentence adds value without redundancy, making it efficiently structured and appropriately sized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 1 parameter with full schema coverage and no output schema, the description is largely complete: it explains the tool's behavior, usage, and output. However, it lacks details on error handling or what happens with invalid project names, leaving a minor gap for a mutation tool with no annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the 'projectName' parameter. The description adds minimal value beyond this, only stating it's required and implying it should come from 'list_projects()'. No additional syntax or format details are provided, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('switch') and resource ('active project context'), specifying it's for multi-project setups. It distinguishes from siblings like 'list_projects' (which lists available projects) and 'current_project' (which likely shows current context), 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is provided: use before operations when managing multiple Optimizely projects, and use 'list_projects()' to see available projects. It also specifies when-not scenarios by implying this is for multi-project contexts only, offering a clear alternative tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes key behavioral traits: it's a diagnostic tool for connection testing, mentions performance characteristics ('REAL-TIME: 2-5s'), specifies what it validates (credentials, environment accessibility), and indicates what it returns (permission levels, accessible environments, project info). It doesn't mention potential side effects or error handling, but covers most essential behavioral aspects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. Every sentence adds value: the first establishes purpose and scope, the second provides usage context, and the third clarifies returns and alternatives. There's minimal redundancy, though the structure could be slightly more organized around distinct functional aspects.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's diagnostic nature and 7 undocumented parameters with no output schema, the description provides good context on purpose and usage but insufficient parameter guidance. It covers behavioral aspects well given no annotations, but the parameter gap is significant. For a connection testing tool with many configuration options, more parameter context would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 7 parameters with 0% description coverage, meaning none of the parameters are documented in the schema. The description only mentions one parameter ('Optional: project') without explaining what 'project' refers to or providing any context for the other 6 parameters (projectId, projectName, apiKey, apiSecret, setupMode, autoFix, skipChecks). This leaves most parameters semantically unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('Test API connection', 'verify credentials', 'validates', 'checks', 'returns') and resources ('API key/secret', 'environment accessibility', 'permission levels', 'accessible environments', 'project info'). It distinguishes itself from sibling tools by explicitly mentioning its diagnostic nature for connection testing versus other operational tools like 'verify_access' for detailed permission checks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('after configuration changes or when troubleshooting connection issues') and when not to use it by naming an alternative ('Use verify_access() for detailed permission checks'). This clearly differentiates it from sibling tools and sets appropriate context for its application.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 does well by specifying the valid range (10-600 seconds), mentioning that changes are 'INSTANT: <1s', and noting it 'Returns updated monitor configuration'. However, it doesn't address important behavioral aspects like whether this requires special permissions, if changes are reversible, or potential rate limit implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured with zero wasted words. It front-loads the core purpose, provides usage guidance, specifies parameters, and mentions the return value - all in four concise sentences. Every sentence adds clear value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description does reasonably well by explaining the action, parameters, and return value. However, it doesn't fully address the complexity of changing monitoring behavior - missing details about permissions needed, whether the change persists, or how it affects system resources. The parameter naming mismatch with the schema is also a completeness issue.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must compensate for the schema's lack of parameter documentation. It successfully explains that 'intervalSeconds' represents 'polling frequency' with a 'Valid range: 10-600 seconds', and mentions 'monitorId' is required. However, it incorrectly names parameters as 'monitorId' and 'intervalSeconds' while the schema uses 'deploymentId' and 'interval', creating some confusion.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Change polling frequency') and resource ('for specific monitor'), distinguishing it from siblings like 'stop_monitoring' or 'get_monitoring_stats'. It goes beyond just restating the name by specifying what aspect of monitoring is being updated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use different interval ranges (lower for urgent deployments, higher for long-running operations), but doesn't explicitly mention when NOT to use this tool or name specific alternatives among the sibling tools. The guidance is helpful but not exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 does well by specifying the operation is 'INSTANT: <1s', that changes 'persist for session', and includes important warnings about credential validity and downstream impacts. It also mentions the return value ('Returns updated project config'). However, it doesn't address permissions, error handling, or whether changes are reversible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded with the core purpose. Each sentence adds value: timing information, what can be modified, persistence, warnings, requirements, return value, and testing recommendation. There's minimal redundancy, though the structure could be slightly more organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with 10 parameters, no annotations, and no output schema, the description provides good behavioral context but insufficient parameter documentation. It covers timing, persistence, warnings, and testing recommendations, which helps compensate for missing annotations. However, the parameter guidance is misleading and incomplete given the low schema coverage, leaving significant gaps in understanding how to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 10% (only 'makeDefault' has a description), so the description must compensate. While it mentions 'Required: projectName, updates (object with fields to change)', this is misleading since the schema shows 0 required parameters and no 'updates' parameter exists. The description lists some parameter categories (credentials, name, environment settings) but doesn't map them to the 10 specific parameters in the schema, leaving most undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'update' and resource 'project configuration settings', specifying what fields can be modified (credentials, name, environment settings). It distinguishes from sibling 'get_project' which presumably reads rather than modifies. However, it doesn't explicitly differentiate from 'switch_project' or other project-related tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for when to use ('modifies stored credentials, project name, or environment settings') and includes a caution about invalid credentials breaking subsequent operations. It also suggests testing with 'test_connection()' after updating. However, it doesn't explicitly state when NOT to use this tool or provide alternatives for specific scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 effectively describes the tool's behavior: real-time performance (2-5s), what it checks (accessible environments), what it returns (detailed permission levels, environment access matrix), and optional caching behavior ('Force re-check even if cached' mentioned in schema). It doesn't cover error conditions or authentication failure responses.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, followed by timing, functionality, usage guidance, and return format. Every sentence adds value with no redundancy. The emoji adds visual distinction without compromising clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter tool with no annotations and no output schema, the description does well covering purpose, behavior, and usage. It explains what the tool returns (environment access matrix with permission levels) despite no output schema. Missing details include parameter relationships and error handling, but overall provides good context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (1 of 5 parameters has a description), so the description must compensate. It mentions 'Optional: project' which helps explain the projectId/projectName parameters, and the overall context clarifies that apiKey/apiSecret are for credential verification. However, it doesn't fully explain all 5 parameters or their relationships.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs ('verify', 'checks') and resources ('API credentials and environment permissions', 'environments'). It distinguishes from siblings by focusing on credential verification rather than deployment, logging, or project management operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly states when to use the tool ('Use before deployment operations to confirm access') and provides context about timing ('REAL-TIME: 2-5s'). This gives clear guidance on when this verification tool should be invoked versus proceeding directly with deployment operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.