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

With no annotations, the description fully discloses behavioral traits: it supersedes other tools, has multiple modes, filtering, summarize, and truncation. It does not mention side effects or safety, but as a read tool, this is adequate.

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 well-structured with modes and args list, front-loading the main purpose. While somewhat lengthy, every sentence adds value; minor room for tightening.

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?

With an output schema present, return values need not be explained. The description covers all parameters and usage scenarios thoroughly, missing only edge cases like empty results. Overall quite complete for a complex 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?

Given 0% schema description coverage, the description thoroughly explains each parameter (config_type, service_filter, filter, summarize, include_values, limit, max_chars) and their interactions, providing significant value beyond 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 explicitly states it is a unified configuration introspection tool that supersedes other similar tools. It clearly describes the function: dump configurations, and differentiates by covering multiple modes and parameters, thus distinguishing from sibling tools which are unrelated.

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 details when to use each mode: single type vs bulk, filtering options, and summarization. It provides clear context on parameter interactions but does not explicitly state when not to use this tool or mention alternatives among siblings, though siblings are not configuration-focused.

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 present, so description bears full weight. Discloses it shows real-time progress and returns success/failure. No side effects mentioned, but for a read-only tool this is sufficient.

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?

Description is verbose with redundant bullet points and repeated phrases. While informative, it could be trimmed without losing 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 parameterless tool with output schema, the description covers purpose, usage triggers, and return format. No gaps given the low 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?

No parameters in schema, so description doesn't need to add parameter info. Schema coverage is 100% vacuously. Baseline 4 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?

Clearly states it retrieves currently active requests/operations in an Ambari cluster. Lists core functions and distinguishes from siblings like get_request_status by focusing on 'active' and 'in progress'.

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?

Provides extensive list of 'Required Usage Scenarios' covering various phrasings. Lacks explicit exclusions or when-not-to-use instructions, but the context is clear.

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 exist, so description carries full burden. It thoroughly explains the two modes, filtering capabilities, pagination, time context, and that it provides current time for LLM calculations. It is transparent about behavior without contradictions.

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 well-structured with clear sections (Tool Role, Core Functions, Usage Scenarios, Args, Returns) and front-loaded key info. However, it is somewhat verbose and has minor redundancy (e.g., first line repeated in Core Functions).

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 14 parameters, no annotations, and an output schema, the description covers all aspects: modes, filtering, pagination, time context, output formats, and return value description. It is complete and leaves no critical gaps.

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 0%, but the description lists all 14 parameters with explanations, mode-specific applicability, and defaults. It adds significant meaning beyond the schema, especially for mode-dependent parameters like maintenance_state, from_timestamp, to_timestamp, page_size, and format.

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 it retrieves current alerts or alert history from Ambari cluster, with two distinct modes. It distinguishes itself from sibling get_current_alerts by also handling history. The verb 'retrieve' and resource 'alerts' are specific.

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 required usage scenarios for both current and history modes, and lists when to use based on user queries. However, it does not include exclusions or when not to use this tool versus siblings like get_current_alerts.

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?

Describes the tool as 'real-time retrieval' with no side effects, and specifies return format (success: formatted info, failure: error message). With no annotations, the description adequately covers behavioral traits for a read-only operation, though it could mention freshness or auth expectations.

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 clear sections and front-loaded purpose. A bit verbose with redundant items like 'formatted output for LLM automation', but still efficient 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 simplicity (no params, output schema exists), the description provides complete context: purpose, usage scenarios, return format. Adequate for an agent to decide and invoke correctly.

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?

No parameters exist, so baseline is 4. The description adds no parameter information beyond the schema, but that is acceptable given zero 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?

Clearly states it retrieves basic information for an Ambari cluster, listing specific fields like name, version, provisioning state, and security type. Distinguishes from siblings by focusing on overall status vs. specific services or hosts.

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?

Provides explicit 'Required Usage Scenarios' with specific triggers (e.g., 'when users request cluster info, status, or summary'). Lacks exclusion criteria or alternative sibling mentions, but the guidance is clear and actionable.

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 real-time retrieval via Ambari REST API, return content (service names, state, cluster info, links, visual indicators), and success/failure format. However, it is verbose and includes ambiguous 'visual indicators' without elaboration. Otherwise, it is adequately transparent.

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 structured with clear sections (Tool Role, Core Functions, Scenarios) and front-loaded with the core purpose. However, it is lengthy and repeats the concept of 'service list with status' multiple times. It earns its place but could be more 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 zero parameters and the presence of an output schema, the description need not explain return values but does so explicitly. It also provides usage and prohibition scenarios, making the tool's context complete for an agent. No gaps are evident.

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?

There are no parameters, and schema coverage is 100% trivially. The baseline score for 0 parameters is 4. The description does not add parameter semantics because none exist, so it meets the baseline without needing compensation.

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 retrieves the list of services with status in an Ambari cluster. It specifies 'all running services' and 'basic status information,' and the 'Required Usage Scenarios' and 'Prohibited Scenarios' effectively distinguish this tool from siblings like get_service_details and get_service_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 explicit 'Required Usage Scenarios' and 'Absolutely Prohibited Scenarios,' offering clear guidance on when to use this tool (e.g., when users mention 'service list') and when not to (e.g., general Hadoop questions, service installation). This directly helps the agent decide among siblings.

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 present, so the description carries full burden. It implies a read operation via 'retrieve', but does not disclose any additional behavioral traits such as rate limits, authentication requirements, or side effects. The deprecation note is helpful but not sufficient for 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 two sentences long, front-loading the purpose and immediately providing deprecation context. Every sentence earns its place 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?

An output schema exists, so return values are documented. However, the description lacks parameter explanations and does not clarify what 'current alerts' means or how filtering works. Given zero annotation coverage, the description is only partially 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 0%, meaning the input schema provides no parameter descriptions. The tool description does not explain any of the 7 parameters (e.g., cluster_name, service_name, state_filter), leaving the agent without guidance on how to use them.

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 'Retrieve current alerts from Ambari cluster', specifying the action and resource. It also distinguishes from sibling by noting deprecation in favor of get_alerts_history.

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 deprecation and provides the alternative get_alerts_history with mode='current', guiding the agent to prefer the replacement while acknowledging backward compatibility.

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 provided, so the description carries the full burden. It discloses that the tool returns hardware specs, state, metrics, components, and formatted output. It does not explicitly state read-only nature or authentication needs, but the behavior is well enough described for most 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?

Well-structured with sections like Tool Role, Core Functions, Required Usage Scenarios. However, some redundancy exists (e.g., Core Functions repeats purpose). The description is front-loaded with the primary action.

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?

Covers both modes (with and without host_name). Mentions return contents (hardware, metrics, state, components). An output schema exists so precise fields are not needed. For a single-parameter tool, this is sufficiently 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 coverage is 0% (no description on host_name param). The description adds significant value by explaining host_name is optional with an example value, and clarifies its role in filtering. This compensates for the missing schema 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?

Fully stated: 'Retrieves detailed information for a specific host or all hosts in the Ambari cluster.' Uses a specific verb and resource, and distinguishes from siblings like list_hosts (which likely only lists names) by specifying scope and detail level.

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?

Provides clear scenarios in 'Required Usage Scenarios' (e.g., when users request host details, auditing). Lacks explicit when-not-to-use or alternative sibling recommendations, but the context is clear enough for an agent to infer appropriate use.

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 explains that the tool returns the full template or a specific section, and a headings mode. It does not mention permissions, error handling, or other behavioral traits, but for a simple read operation, the description is sufficiently transparent.

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 concise, with the main purpose in the first sentence, followed by a brief note on project decision and parameter details. Every sentence adds value, with no unnecessary 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 existence of an output schema, the description does not need to explain return values. It covers the parameters thoroughly, and the tool's complexity is low (2 optional params). The description is complete for an agent to understand and invoke the tool correctly.

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 0%, so the description must compensate. It does so by explaining both parameters: 'section' (optional section number or keyword) and 'mode' (if 'headings' returns heading list). This adds meaningful context beyond the schema's basic type definitions.

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: 'Return the canonical English prompt template (optionally a specific section).' The verb 'Return' and resource 'prompt template' are specific, and the tool is distinct from siblings which deal with different domains like cluster management or metrics.

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 explains the project decision (only one file) and the optional parameters, providing context for usage. However, it does not explicitly state when to use this tool over alternatives or when not to use it. Since it is the sole tool for this purpose, the guidance is adequate but lacks explicit exclusion or 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?

No annotations are provided, so the description bears the full burden. It explains the tool returns status, progress, timing, and is intended for automation. It does not disclose authorization needs or side effects, but for a read-only operation this is adequate.

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 well-structured with sections, but somewhat verbose. It could be more concise without losing key information. Overall it is clear and logically 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?

Given the presence of an output schema, the description adequately outlines return values (status, progress, timing). It lacks details on error conditions or retry logic, but is sufficient for a simple status retrieval 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 description explains the 'request_id' parameter's purpose and type (int), but the input schema declares it as a string. This contradiction could mislead an agent. Since schema coverage is 0%, the description adds some meaning, but the inconsistency reduces reliability.

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 'Retrieves the status and progress of a specific Ambari request operation', using a specific verb and resource. It distinguishes itself from siblings like 'get_active_requests' and 'get_request_tasks' by focusing on a single request by ID.

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 'Required Usage Scenarios' section lists clear conditions for use, such as when users ask for status or during monitoring. However, it does not explicitly contrast with sibling tools like 'get_request_tasks' that might be more appropriate for detailed task-level information.

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?

The description details the behavior: listing tasks with filtering capabilities and return format. However, it does not explicitly state that the tool is read-only or mention authentication needs. Since annotations are absent, the description carries full burden but is still thorough.

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 well-structured with sections and front-loaded purpose. However, it is fairly long; while every sentence is useful, slight trimming could improve conciseness without losing 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?

Given the tool's complexity (multiple filters, use cases), the description covers all necessary aspects: parameters, return format (table vs error), and usage scenarios. No output schema is needed as the description explains the output.

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 fully compensates by explaining each parameter: request_id as integer string, status_filter with exact statuses and 'not:' prefix logic, host_filter as substring. This adds critical meaning beyond the bare 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 retrieves task-level details for a specific Ambari request with a host-by-host breakdown, and it explicitly differentiates from the sibling tool 'get_request_status' which provides summary-level 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 'Required Usage Scenarios' section explicitly lists when to use this tool, such as debugging partially-failed operations or when request progress is near 100% but incomplete. It provides clear context for use vs. 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?

No annotations are provided, so the description carries the burden. It states it retrieves data and returns formatted output or errors, implying read-only behavior. However, it lacks details on permissions, idempotency, or potential side effects, making it adequate but not complete.

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 well-structured with clear sections including role, core functions, required scenarios, args, and returns. It is front-loaded with the main purpose and contains no unnecessary 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 (one parameter) and presence of output schema, the description covers purpose, usage, and return format adequately. It mentions failure behavior. A slight gap is not discussing authentication or permissions, but overall it is 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 0% schema description coverage, the description adds value by specifying service_name with examples (e.g., 'HDFS', 'YARN'). This goes beyond the schema's bare property type, compensating for the lack of schema-level 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 it retrieves detailed components information for a specific service in the Ambari cluster. The verb 'retrieves' and resource 'components information' are specific, and it distinguishes from siblings like get_service_details by focusing on component-level details.

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 'Required Usage Scenarios' section provides explicit guidance on when to use, such as when users request component details or troubleshooting health. However, it does not mention when not to use or alternative tools, which prevents 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?

No annotations provided; description implies read-only behavior but does not explicitly state idempotence, safety, or side effects. Mentions 'formatted output for LLM automation' but no permission or rate limit 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?

Structured with sections but contains redundancy (e.g., 'Retrieves detailed status and configuration information' repeated in opening and Core Functions). Could be tighter.

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?

Single-parameter tool with existing output schema; description covers success and failure return types. Lacks details on output fields but is acceptable given output schema.

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 has 0% description coverage, but description adds examples ('HDFS', 'YARN', 'HBASE') and clarifies purpose beyond the bare schema type 'string'.

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 'Retrieves detailed status and configuration information for a specific service' and differentiates from siblings like get_service_status and get_service_components by emphasizing comprehensive details.

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?

Provides explicit 'Required Usage Scenarios' (detailed info requests, troubleshooting) but lacks comparative guidance on when to use alternatives like get_service_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?

No annotations are provided, so the description must carry the full burden. It mentions real-time retrieval and state information but does not explicitly declare the tool as read-only or discuss side effects, permissions, or error behavior beyond a generic failure message.

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 well-structured with sections and bullet points but is somewhat verbose, repeating concepts like 'status' and 'state'. It could be more concise without losing 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 simple retrieval tool with one parameter, the description covers purpose and parameter adequately. However, it does not address when to use this tool versus similar siblings (e.g., get_service_details), and the output description is vague despite an output schema being present.

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 parameter service_name is clearly described with examples (e.g., 'HDFS', 'YARN', 'HBASE'), adding practical value beyond the schema which lacks a description field. Schema description coverage is 0%, so the description compensates well.

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 it retrieves status information for a specific service in an Ambari cluster, with a specific verb and resource. It distinguishes itself from sibling tools like get_service_details or get_cluster_services by focusing on real-time status and state.

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 includes 'Required Usage Scenarios' such as when users ask about specific service status, troubleshooting, and monitoring. However, it does not explicitly compare to sibling tools, leaving some ambiguity about when to use this tool over others like get_service_details.

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?

The description implies a read-only operation ('Get detailed information') but does not explicitly state safety or side effects. With no annotations, the burden is on the description; it partially discloses the return content but omits auth requirements, rate limits, or potential 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 concise, with a brief introductory sentence followed by structured sections for Args and Returns. It is front-loaded with the core purpose and uses minimal, efficient language.

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 presence of an output schema, the description does not need to detail return values, but it lists the categories of information. The tool is simple with one parameter, and the description covers its basic usage. However, it lacks any mention of error cases or prerequisites.

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, but the description's 'Args' section explains that user_name is 'The username to retrieve details for'. This adds meaningful context beyond the bare schema type, compensating for the lack of 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 'Get detailed information about a specific user' with a specific verb and resource. It lists the categories of information returned (profile, permissions, authentication sources). However, it does not distinguish itself from the sibling tool 'list_users', which likely retrieves multiple users.

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?

No guidance is provided on when to use this tool versus alternatives like 'list_users'. The description only states the function and requires a user_name, but does not explain scenarios or contexts for use.

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 must convey behavioral traits. While 'report' implies a read operation, there is no explicit mention that it is non-destructive, no disclosure of authentication needs, rate limits, or potential side effects. The description's brevity leaves significant behavioral ambiguity.

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 a single sentence, which is concise, but it lacks structure. While it is not verbose, it does not efficiently front-load key details; it is under-specified rather than concisely informative.

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 complexity of a tool that produces a report from Ambari metrics, the description is too minimal. It does not explain what the report contains beyond 'capacity and DataNode', does not describe parameter effects, and omits any usage context or prerequisites. The existence of an output schema partially compensates, but overall the description is incomplete.

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, and the description does not mention any of the two parameters (cluster_name, lookback_minutes). It fails to add any meaning or context beyond the parameter names and types, leaving the agent unable to understand how to use them.

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 produces a DFSAdmin-style capacity and DataNode report using Ambari metrics. The verb 'produce' and specific resource 'DFSAdmin-style capacity and DataNode report' differentiate it from sibling tools which deal with configurations, requests, alerts, and services.

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 no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, contexts, or exclusions for usage, leaving the agent without criteria to decide if 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?

No annotations are provided, so the description carries the burden. It implies a read-only operation by stating it returns data, but does not explicitly confirm it is non-destructive or disclose any behavioral traits beyond the basic output.

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 a single, efficient sentence with only 9 words, conveying the core functionality without redundancy. However, it could be expanded slightly to improve clarity on parameters.

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 simple tool with three parameters and an output schema, the description lacks detail on parameter behavior and usage context. It does not address when to use refresh or limit, leaving gaps for 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?

With 0% schema description coverage, the description must compensate but only partially addresses one parameter: 'optionally with metric counts' hints at include_counts. The refresh and limit parameters are not explained at all.

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 that the tool returns 'discovered AMS appIds' and allows including metric counts. It uses a specific verb 'Return' and identifies the resource, but does not explicitly differentiate from sibling tools like list_ambari_metrics_metadata or list_common_metrics_catalog.

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 no guidance on when to use this tool versus alternatives, nor any prerequisites or context. It simply describes the output without indicating appropriate use cases.

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, and the description only states it retrieves metadata, lacking disclosure on permissions, rate limits, pagination, or response structure beyond what the output schema offers.

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?

Single sentence with no waste, but could include more detail without sacrificing conciseness.

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 6 parameters and no schema descriptions, the description is too brief; it does not explain what metric metadata is or how filters affect results.

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 does not explain any of the 6 parameters, failing to add meaning beyond parameter names and types.

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 'retrieve', resource 'metric metadata', and source 'Ambari Metrics service', distinguishing it from sibling tools like query_ambari_metrics and list_ambari_metric_apps.

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?

No guidance on when to use this tool vs alternatives; the description only mentions optional filters without providing context on preferred use cases.

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 only states the basic function and does not disclose any behavioral traits such as how null appId is handled or safety.

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 one concise sentence, but it lacks structure and does not cover the tool's complexity. It is front-loaded but under-specified.

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 five parameters and output schema, the description is too brief. It fails to explain how to use parameters effectively, making the tool incomplete 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 and no elaboration in the description, the agent is left to infer the meaning of parameters like search, limit, min_score, and include_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 it lists supported metrics per appId with exact names only, distinguishing it from similar tools like list_ambari_metric_apps.

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 implies usage for retrieving supported metrics by appId but provides no explicit guidance on when to use this tool versus siblings like list_ambari_metrics_metadata.

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 provided, so description carries burden. It mentions querying Ambari REST API and returning formatted output, but doesn't disclose potential side effects, rate limits, or authentication needs. Adequate but not exhaustive.

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?

Description is well-structured with headings (Tool Role, Core Functions, Required Usage Scenarios, Returns) and is concise without unnecessary content.

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 is simple with no parameters and has an output schema. Description covers purpose, functions, usage scenarios, and return format, making it complete for the 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?

Tool has zero parameters, and schema coverage is 100%. Per guidelines, baseline is 4. Description does not need to add parameter info.

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?

Description clearly states 'Retrieves the list of hosts in the Ambari cluster.' It uses a specific verb and resource, and differentiates from sibling tools like get_host_details by focusing on listing all hosts.

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?

Description includes 'Required Usage Scenarios' (e.g., when users request host list, auditing), indicating when to use. However, it does not explicitly state when not to use or mention alternatives like get_host_details.

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 exist, so the description must carry the full burden. It only states it returns a formatted list, but does not mention read-only nature, authentication needs, or potential side effects.

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

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

Two brief sentences that are front-loaded with the action and scope, containing no extraneous 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 parameterless list tool with an output schema, the description adequately covers its purpose. It could mention that it is a read operation, but overall it is 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?

No parameters exist, so schema coverage is 100%. The description adds no parameter info, but none is needed. Baseline 4 applies.

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 'List all users in the Ambari system,' which is a specific verb+resource. It distinguishes from sibling 'get_user' by implying listing all vs. a single user.

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?

No explicit guidance on when to use this tool versus alternatives like 'get_user' is provided. The usage is implied but not clarified.

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 exist, so the description bears full responsibility for behavioral disclosure. It only mentions the constraint 'exact metric names only' but does not address data volume limits, rate limiting, authentication requirements, or other behavioral traits.

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 a single sentence, concise but overly brief. It front-loads the action but lacks necessary detail. Given the tool's complexity, the sentence is too short to be effective.

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?

Despite the presence of an output schema, the description fails to provide context for the numerous parameters or the exact nature of the returned metrics. It covers only the basic purpose, leaving many aspects unexplained.

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 and 12 parameters (including optional ones like app_id, hostnames, duration), the description does not explain any parameter. The agent must infer parameter usage from names alone, which is insufficient.

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 explicitly states 'Fetch time-series metrics (exact metric names only) from Ambari Metrics,' which clearly identifies the verb (fetch), resource (time-series metrics), and constraint (exact metric names). It distinguishes itself from sibling tools like 'list_ambari_metrics_metadata' and 'list_ambari_metric_apps'.

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?

No guidance is provided on when to use this tool versus alternatives, such as listing metrics first or using other query tools. The description simply states what it does without contextual usage advice.

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 the full burden. It discloses the stop-all-then-start-all behavior, waiting for completion, and return messages. However, it omits details about whether the operation is synchronous or asynchronous, or potential side effects like service downtime.

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 uses a structured format with labeled sections (Tool Role, Core Functions, etc.), which aids readability but adds verbosity. Some redundancy exists (e.g., explaining the stop-start sequence twice). Could be more 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 parameters and presence of an output schema, the description sufficiently explains purpose, usage, and return format. It lacks mention of prerequisites or authorization, but these are not critical for a restart tool. Overall adequate.

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 zero parameters, so the description does not need to add parameter meaning. The baseline is 4 as no parameters are present.

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 defines 'restart_all_services' as a dedicated tool for automated bulk restart of all Ambari services, specifying the stop-then-start sequence. It distinguishes itself from sibling tools by explicitly being for 'all services' vs. single-service 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?

The description lists required usage scenarios such as when users request 'restart all services' or for maintenance. It provides clear context but does not explicitly exclude cases where single-service restart tools (e.g., 'restart_service') would be more 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?

Describes stop-then-start process, wait for completion, and return info. No annotations provided, but description covers key 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?

Concise yet comprehensive with clear sections (Tool Role, Core Functions, Required Usage Scenarios, Args, Returns) and no unnecessary text.

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?

Covers all necessary context: parameters, behavior, return values, and usage scenarios. Could be slightly more complete regarding error details, but adequate.

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 has 0% description coverage, but description provides examples and explanation for host_name and component_name, adding value beyond 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?

Clearly states 'Restarts a specific component on a specific host' with verb and resource, and distinguishes from siblings like restart_service, start_host_component, etc.

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 lists when to use (component restart requests, recovery, config changes) and implies when not to via sibling 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?

No annotations are provided, so the description carries the full burden. It explains the stop-start sequence, waiting for completion, and return messages. However, it does not mention permissions, side effects, or concurrency considerations, which would enhance 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 structured with sections like [Tool Role], [Core Functions], and [Required Usage Scenarios], making it front-loaded with key information. However, it is somewhat verbose and includes redundancy (e.g., Args section repeats 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 the tool's simplicity (single parameter, no annotations, but output schema exists), the description provides comprehensive information: behavior, scenarios, and return format. The agent can confidently invoke the tool based on this description alone.

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 1 parameter (service_name) with 0% description coverage. The description adds: 'Name of the service to restart (e.g., "HDFS", "YARN")', providing example values that compensate for the lack of schema documentation. It does not add constraints but is helpful.

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 it restarts a specific Ambari service with a stop-then-start sequence. It distinguishes from siblings like start_service, stop_service, and restart_all_services by focusing on the single-service restart action.

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 lists required usage scenarios: when users request 'restart', troubleshooting, or maintenance. However, it does not explicitly state when not to use this tool versus alternatives like restart_all_services, though the scenarios provide sufficient 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool returns progress tracking info and error messages, but does not mention prerequisites, potential side effects, or authorization needs, which is acceptable for a non-destructive start 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 well-structured with sections and front-loaded with the main purpose. It is slightly verbose but every section adds value and maintains 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?

Given no annotations, zero parameters, and an output schema mentioned, the description fully covers the tool's functionality, return values, and usage scenarios, making it complete for an automated 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 no parameters (0 params), so the description correctly adds no additional parameter information. Per rules, baseline for 0 params is 4.

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 starts all services in an Ambari cluster, with a specific verb (starts) and resource (all services). It distinguishes from siblings like start_service and restart_all_services by emphasizing bulk startup.

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 'Required Usage Scenarios' section lists explicit contexts where this tool should be used, such as cluster startup or recovery. However, it does not explicitly mention when not to use it or name alternative tools for single service 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?

Without annotations, the description carries the burden. It discloses key behaviors: the component is started only if not already STARTED ('Skip if already in STARTED state'), and it returns request information for progress tracking. It also mentions fine-grained control without affecting other hosts. This provides adequate transparency for a mutation tool.

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

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

The description is well-structured with headings ([Tool Role], [Core Functions], etc.) and front-loads key information. While it is somewhat verbose, each section provides necessary detail without redundancy. It could be slightly more concise, but it's effective.

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 simplicity of two string parameters, the presence of an output schema, and sibling context, the description covers all essential aspects: purpose, usage scenarios, core functions (with idempotency), parameter examples, and return value. It is complete for an agent to select and invoke correctly.

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% description coverage, but the description includes an 'Args' section with examples for each parameter (e.g., host_name: 'hdp-node-01.example.com', component_name: 'DATANODE', 'NODEMANAGER'). These examples clarify the expected format and meaning, adding value beyond 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 explicitly states 'Starts a specific component on a specific host in the Ambari cluster', with clear verb and resource. It distinguishes from sibling tools like start_service and restart_host_component by noting it's a 'Dedicated tool for starting individual host-level components, enabling fine-grained control without affecting other hosts or the overall service.'

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 includes a 'Required Usage Scenarios' section listing three specific scenarios when to use this tool (e.g., 'when a specific host's component is STOPPED but the overall service is STARTED'). It does not explicitly state when not to use it, but the scenarios imply appropriate contexts, and sibling tools provide 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?

No annotations are provided, so the description carries the full burden. It describes the action ('initiate Ambari request'), return types (success with request info, failure with error message), and mentions 'safe and monitored startup'. However, it does not disclose potential side effects, authentication needs, or prerequisites (e.g., service must be stopped). This is adequate but not highly transparent.

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 well-structured with sections (Tool Role, Core Functions, etc.), making it easy to scan. It is somewhat lengthy but each section adds useful information. Could be slightly more concise without losing 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 simple single-parameter tool, the description covers the core action, return types, and usage scenarios. It does not mention output schema details (though context indicates an output schema exists), but the description already explains the return format. It lacks prerequisites or edge cases, but overall is sufficiently complete 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 input schema has one required parameter (service_name) with no description. The description adds value by providing examples ('HDFS', 'YARN', 'HBASE') and a clear purpose. With schema description coverage at 0%, this compensation is strong, though it could include format constraints or allowed values.

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 it 'Starts a specific service in the Ambari cluster' using a specific verb and resource. The 'Core Functions' and 'Required Usage Scenarios' further reinforce the purpose and differentiate it from sibling tools like stop_service, restart_service, and start_all_services.

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?

It explicitly lists required usage scenarios (e.g., when users request to start a service, recovering stopped services). It does not directly state when not to use, but the naming of sibling tools implies alternatives (e.g., start_all_services for bulk). The guidance is clear but could be slightly more explicit about exclusions.

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 discloses the tool's bulk stopping behavior and return value (request info or error message). However, it does not mention the destructive nature (all services stopped), whether it requires confirmation, or any prerequisites like cluster state. This leaves some behavioral gaps.

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

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

The description is structured with clear sections (role, core functions, usage scenarios) and is front-loaded with purpose. Some phrases are slightly redundant (e.g., 'Dedicated tool' and 'bulk stopping'), but overall it is concise and well-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?

Given the tool has no parameters and an output schema (likely documented elsewhere), the description covers the core behavior, return value, and usage scenarios. It doesn't mention limitations or side effects beyond what is implied, but for a simple action tool, it is sufficiently 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?

The tool has zero parameters, and the input schema is empty with 100% coverage. The description does not need to add parameter meaning, and it properly avoids mentioning non-existent parameters. Baseline 4 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 stops all services in an Ambari cluster, using the exact phrase 'Stop All' from the Ambari Web UI. It distinctively sets this tool apart from siblings like 'stop_service' (single service) and 'start_all_services' (opposite action).

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 lists required usage scenarios like 'stop all services', 'stop everything', and 'cluster shutdown', making it clear when to use. It does not explicitly exclude other scenarios, but the context implies it should not be used for stopping individual services.

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 provided, so description carries full burden. It discloses that it skips if the component is already in INSTALLED state and returns request info for progress tracking. However, it doesn't detail authorization needs or side effects beyond stopping the component.

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 well-structured with clear sections (Tool Role, Core Functions, etc.) and is front-loaded with the main purpose. However, there is some redundancy (first sentence restated in Tool Role), and it could be slightly more 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 the simple input schema (two strings) and existence of output schema, the description provides adequate context. It covers core functions and usage scenarios, though could mention error handling or prerequisites like host existence. Overall, it is fairly complete for a straightforward 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 coverage is 0%, so description adds significant value: host_name is defined as 'Hostname where the component resides' with an example, and component_name as 'Name of the component to stop' with examples like 'DATANODE'. This compensates for the lack of 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 stops a specific component on a host, using specific verbs and resources. It distinguishes from sibling tools like 'start_host_component' and 'restart_host_component', and provides examples like 'stop DataNode on host-A'.

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 'Required Usage Scenarios' section explicitly states when to use, e.g., when users request to stop a component on a specific host, decommissioning, or troubleshooting. It contrasts with broader service-level operations, and mentions the skip-if-already-stopped behavior.

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 fully carries the burden. It details behavioral traits including safe and monitored shutdown, return of request info for progress tracking, and clear success/error messages.

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 well-structured with sections like [Tool Role] and [Core Functions], but it is somewhat verbose. It front-loads the purpose effectively.

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 single parameter and presence of output schema (mentioned in description), the description fully explains the return value structure and covers all necessary context for a stop operation.

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 single parameter service_name has 0% schema description coverage. The description adds meaning by stating it is the name of the service to stop and provides examples (e.g., HDFS, YARN).

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 it stops a specific service in the Ambari cluster, using the verb 'stops' and the resource 'service'. It distinguishes from siblings like start_service and restart_service.

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 lists required usage scenarios such as when users request to stop a service or during maintenance, providing clear guidance on when to use this tool.

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