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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: execution as a background job and return of a job ID, but lacks details on permissions, rate limits, error handling, or job lifecycle implications. It adequately covers the core operation but misses advanced 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 front-loaded with the core purpose in the first sentence, followed by structured Args and Returns sections. Every sentence adds value without redundancy, making it highly efficient 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's moderate complexity (background execution), no annotations, and an output schema (ExecuteOutput), the description is mostly complete. It covers purpose, parameters, and returns, but could benefit from more behavioral context like security implications or job management links.

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 minimal semantics beyond the schema (which has 100% coverage), noting the command is a 'Shell command to execute in the background,' slightly reinforcing the schema's description. With only one parameter, the baseline is high, but it doesn't provide format examples or constraints.

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

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

The description clearly states the specific action ('Execute a command as a background job') and resource ('command'), distinguishing it from sibling tools like get_job_output or kill_job by focusing on job initiation rather than monitoring or termination.

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 starting background jobs, with context from sibling tools suggesting alternatives for job monitoring (get_job_status, tail_job_output) and management (kill_job, interact_with_job). However, it lacks explicit guidance on when to use this versus other job-related tools or prerequisites.

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 retrieves 'complete' output, which is a useful behavioral trait beyond basic functionality. However, it does not mention potential issues like large output handling, permissions required, or rate limits, leaving gaps in behavioral context.

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

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

The description is well-structured and front-loaded with the core purpose in the first sentence. The Args and Returns sections are concise and directly relevant, with no wasted words. Every sentence earns its place by clarifying inputs and outputs efficiently.

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 (single parameter) and the presence of an output schema (Returns section), the description is mostly complete. It covers the purpose, input, and output, but lacks details on behavioral aspects like error handling or performance considerations, which could be useful despite the 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?

The schema description coverage is 100%, so the schema already documents the job_id parameter. The description adds minimal value by restating the parameter in the Args section, but it does not provide additional semantics like format details or examples. With high schema coverage, the baseline is 3, but the explicit Args section slightly enhances clarity, warranting a 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 specific action ('Get') and resource ('complete stdout and stderr output of a job'), distinguishing it from siblings like get_job_status (which returns status, not output) and tail_job_output (which likely streams partial output). The verb+resource combination is precise 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 implies usage when you need the full output of a job, but it does not explicitly state when to use this tool versus alternatives like tail_job_output (e.g., for streaming vs. complete output) or list_jobs (for job metadata). Guidelines are implied by the tool's purpose but lack explicit comparisons or 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 carries the full burden. It discloses that this is a read operation (checking status) and lists possible status values (running, completed, failed, killed), which helps understand behavior. However, it lacks details on permissions, rate limits, or error handling, which are important for a job status 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 and front-loaded with the core purpose, followed by clear 'Args' and 'Returns' sections. Every sentence is necessary and contributes to understanding, with no wasted words, making it highly efficient.

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

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

Given the tool's low complexity (single parameter) and the presence of an output schema (implied by 'Returns' section), the description is mostly complete. It covers the purpose, parameter, and return values adequately. However, it could improve by addressing usage relative to siblings or adding behavioral details like error cases.

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 description coverage is 100%, so the schema already documents the 'job_id' parameter. The description adds minimal value by specifying it as a 'UUID', which clarifies the format beyond just 'string'. This slight enhancement justifies a score above the baseline of 3.

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 ('Get the current status') and resource ('a background job'), distinguishing it from siblings like 'get_job_output' (which retrieves output) or 'kill_job' (which terminates jobs). It precisely defines the tool's function without ambiguity.

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 when needing to check job status, but does not explicitly state when to use this tool versus alternatives like 'list_jobs' (for overview) or 'tail_job_output' (for real-time monitoring). No exclusions or prerequisites are mentioned, leaving some context gaps.

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 mentions sending input and returning immediate output, but lacks details on behavioral traits such as whether this requires specific job states (e.g., running), if it blocks until output is available, potential rate limits, or error handling. For a tool that interacts with processes, this is a significant gap in transparency.

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

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

The description is front-loaded with the core purpose in the first sentence, followed by structured sections for Args and Returns. Each sentence earns its place by clarifying parameters and return values without redundancy, making it efficient 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 complexity of job interaction, no annotations, and an output schema (implied by 'Returns' section), the description is mostly complete. It covers purpose, parameters, and return values, but lacks behavioral context like job state requirements or error scenarios, which would be beneficial for full completeness.

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

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 (job_id and input) with descriptions. The description adds minimal value beyond the schema by reiterating that job_id is a UUID and input is text for stdin, but doesn't provide additional semantics like format constraints or examples. Baseline 3 is appropriate as the schema does the heavy lifting.

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

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

The description clearly states the specific action ('Send input to a job's stdin') and resource ('a job'), distinguishing it from siblings like get_job_output (which retrieves output without sending input) or kill_job (which terminates a job). The verb 'send' and resource 'job's stdin' are precise 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 implies usage context by specifying 'send input to a job's stdin,' suggesting it's for interacting with an active job, but it doesn't explicitly state when to use this versus alternatives like get_job_output (for reading output without input) or execute_command (for starting new jobs). No exclusions or prerequisites are mentioned, though 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is to 'terminate' a job, implying a destructive operation, but doesn't clarify critical aspects like whether the kill is reversible, what permissions are required, or potential side effects (e.g., data loss). This leaves significant gaps for a mutation tool.

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

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

The description is highly concise and well-structured: a clear purpose statement followed by brief sections for Args and Returns. Every sentence earns its place, with no redundant information, 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?

Given the tool's complexity (a destructive operation) and the presence of an output schema (which handles return values), the description is moderately complete. It covers the basic purpose and parameter, but lacks behavioral details like safety warnings or prerequisites, which are important for a kill operation 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?

The schema description coverage is 100%, so the schema already documents the job_id parameter. The description adds minimal value by restating it as 'The UUID of the job to terminate', which slightly reinforces the parameter's purpose but doesn't provide additional syntax or format details 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 clearly states the specific action ('Kill') and target resource ('a running background job'), distinguishing it from sibling tools like get_job_status, list_jobs, or get_job_output. It precisely communicates the tool's function without ambiguity.

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 context by specifying 'a running background job', suggesting this tool is for active jobs rather than completed ones. However, it lacks explicit guidance on when to use it versus alternatives like interact_with_job or when not to use it (e.g., for non-running jobs).

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: returns a list with specific fields (job ID, status, command, start time) and sorting by start time (newest first). However, it lacks details on pagination, rate limits, or error handling, which are relevant for a list 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 core purpose in the first sentence, followed by specific details in a second sentence. Every sentence adds value: the first defines the action, and the second clarifies output format and sorting. 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 low complexity (0 parameters, output schema exists), the description is mostly complete. It covers purpose, output fields, and sorting. However, with no annotations, it could benefit from mentioning any limitations (e.g., large result sets) or prerequisites, though the output schema may handle return values.

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 no parameter documentation is needed. The description appropriately adds no parameter information, focusing on output semantics instead. Baseline is 4 for zero parameters, as it avoids unnecessary 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 verb ('List') and resource ('all background jobs'), and distinguishes from siblings by focusing on comprehensive listing rather than individual job operations like get_job_status or kill_job. It specifies the scope includes all jobs with their 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 implies usage for viewing all jobs, which contrasts with siblings that target specific jobs (e.g., get_job_status, kill_job). However, it does not explicitly state when to use this tool versus alternatives like get_job_status for individual checks, leaving some ambiguity.

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. It discloses the tool's read-only nature (implied by 'Get') and the lines parameter constraints (1-1000, default 50), but lacks details on permissions, rate limits, error conditions, or whether the job must be active. It adds some behavioral context but is incomplete for a tool that interacts with job execution.

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 structured Args and Returns sections. Every sentence earns its place by providing essential information without redundancy. The formatting is clear and efficient, 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?

Given the tool's moderate complexity (2 parameters, job interaction), no annotations, and the presence of an output schema (Returns section), the description is mostly complete. It covers purpose, parameters, and return values, but lacks behavioral details like error handling or job state requirements, which would be beneficial for full contextual understanding.

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 'lines' refers to 'Number of lines to return' for both stdout and stderr, and specifies the range (1-1000) and default (50), which enhances understanding beyond the schema's basic documentation. However, it does not explain the 'job_id' parameter further.

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 ('Get the last N lines') and resource ('stdout and stderr from a job'), distinguishing it from siblings like get_job_output (likely full output) and get_job_status (status only). The verb 'tail' is precise and matches the tool name, providing immediate understanding of its function.

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 viewing recent job output, but does not explicitly state when to use this tool versus alternatives like get_job_output or get_job_status. No guidance is provided on prerequisites, such as needing a running or completed job, or exclusions for when not to use it.

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