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

With no annotations provided, the description must disclose behavioral traits. It states the action and return format, but it does not mention that deletion is irreversible, whether permissions are needed, or what happens if the job is not in a queued/running state. This is a mutation tool, so more safety context is expected.

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 short sentences: one for purpose and one for return format. It is front-loaded and contains no fluff, earning its place.

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

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

Although the tool is simple with one parameter, the description is incomplete: it does not explain the parameter's meaning, any required permissions, or edge cases (e.g., what happens if the job is already completed). The presence of an output schema reduces the need to describe returns, but the description still goes beyond that, yet misses critical operational context.

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

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

The schema has zero description coverage for the single parameter job_id, and the description does not explain what job_id refers to or how to obtain it. The return message mentions 'job_id' but not its meaning as input. The description fails to compensate for the schema's lack of parameter documentation.

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

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

The description clearly states the tool's action: 'Delete (cancel) a queued or running job.' This is a specific verb and resource, and it distinguishes this tool from siblings like submit_job, list_jobs, and get_job_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?

There is no guidance on when to use this tool versus alternatives, nor any mention of exclusions or prerequisites. The phrase 'queued or running' implies it is for active jobs, but it does not explicitly say when not to use it or point to alternative tools.

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 clearly states the output type and nature (shell script string, template), and the list of rscgrps adds system-specific context. It does not disclose edge-case behavior like invalid inputs, but the non-destructive nature is apparent.

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 three sentences: purpose, resource groups, and output. It is front-loaded with the main action and avoids unnecessary phrases, though the resource group list adds unavoidable length.

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?

The description adequately explains the tool's purpose and output for a template generator, aided by the presence of an output schema. However, the lack of parameter documentation and annotation makes it less complete than needed for a tool with 8 configurable parameters.

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

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

Schema description coverage is 0%, so the description must compensate for all 8 parameters. It only addresses the rscgrp parameter by listing valid values; no other parameters (gpu, cores, elapse, job_name, work_dir, mpi_procs, extra_pjm_directives) are explained. This leaves most parameters underspecified.

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 generates a PJM job script template for Genkai, and further clarifies it returns a shell script string with #PJM directives. This distinguishes it from siblings like submit_job or list_files.

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 creating a job template without submitting, as it mentions 'ready to submit with pjsub,' but does not explicitly name alternatives or exclusions. The listing of available rscgrps provides helpful context for choosing the correct resource group, giving clear context without formal when/not 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 burden. It discloses the return format (list of job dicts, same as list_jobs) and error behavior (raises RuntimeError if not found). However, it does not explicitly state read-only nature or any side effects, though the wording implies a safe read.

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?

Three concise sentences: purpose, return format, error handling. No wasted words, and the most important information is front-loaded.

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

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

Given the tool's simplicity (one parameter) and the presence of an output schema, the description sufficiently covers the return format and error case. It lacks explicit guidance on when to use it versus alternatives, but that is not strictly required for a simple getter.

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 only parameter, job_id, is self-explanatory ('by ID') and the schema already provides its type and title. With 0% schema description coverage, the description adds minimal extra meaning beyond restating that the ID identifies the job. No format or examples are given.

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 action ('Get status') and the resource ('a specific job by ID'), making it distinct from sibling tools like list_jobs which list all jobs. It's specific and immediately understandable.

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 have a job ID and need status), but it does not explicitly mention alternatives or conditions when not to use this tool. The comparison with list_jobs is implicit rather than an explicit guideline.

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 must carry the full burden of behavioral disclosure. It does mention the return format (a dict with sections), implying a read operation, but it does not explicitly state that the tool is read-only, lacks side effects, or requires any authentication/permissions. This is insufficient 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 concise and well-structured. It opens with a clear action statement, then briefly clarifies the return structure. Every sentence adds value, with no unnecessary detail or repetition, making it easy to scan and understand.

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 need not detail return values, but it still leaves significant gaps: the sole parameter is undocumented, usage guidelines are missing, and no context is provided about when to use this tool. While the tool is simple, the description is incomplete for effective agent selection and invocation.

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%, and the description does not mention the 'rscgrp' parameter at all. As a result, the description adds no meaning beyond the raw schema, failing to compensate for the low coverage. The parameter's purpose, allowed values, and effect on the output are completely unexplained.

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

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

The description clearly states the tool's purpose with a specific verb and resource: 'Get quota and limit information for the current user.' It further details the return structure (sections USER, GROUP, ALL), making it distinct from sibling tools like get_resource_groups or list_resource_groups.

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, no prerequisites, and no mention of conditions under which it should be invoked. There is no reference to sibling tools or exclusions, leaving the agent to infer usage context solely from the name.

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 of behavioral disclosure. It explains the return format (list of dicts with keys) and the optional filter behavior, which are useful behavioral details. It does not mention side effects or state changes, but as a read-only list operation, the 'List' verb implies safety and the return format disclosure 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?

The description is concise and well-structured: a leading summary sentence, a parameter explanation, and a return format specification. Every line earns its place, with no unnecessary fluff or redundancy.

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

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

For a simple one-optional-parameter list tool with an output schema, the description covers purpose, filtering, and return structure. However, it does not explicitly differentiate from the sibling 'list_resource_groups' beyond listing sizes, and it omits potential details like whether all groups are returned by default or if the filter affects only results. These are minor gaps 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 zero description coverage for the 'rscgrp' parameter, so the description compensates by explaining it as 'filter by specific resource group name.' This adds meaning beyond the bare schema, though it could be more specific about pattern matching or case sensitivity.

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

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

The description clearly states the tool's purpose: 'List available resource groups and their sizes on Genkai.' It uses a specific verb ('List'), identifies the resource ('resource groups and their sizes'), and distinguishes itself from the sibling tool 'list_resource_groups' by explicitly mentioning sizes.

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 context for when to use this tool (to list resource groups with sizes) and how to filter with the 'rscgrp' parameter, but it does not explicitly compare against the sibling tool 'list_resource_groups'. No exclusions or alternatives are named, so the usage guidance is implied rather than explicit.

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 must disclose behavior fully. It states the return format (list of dicts with path, name, is_dir) and defaults for directory and pattern, which is useful. However, it omits mention of the max_entries parameter, does not explicitly state it is a read-only operation (though implied), and leaves ambiguity about whether directories are included despite 'list files' and the is_dir return field.

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 extremely concise, using only three lines to convey purpose, parameters, and return format. Every sentence adds value, and it is front-loaded with the purpose statement. This is an example of efficient writing.

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?

The tool is simple and has an output schema, so the description does not need to explain return values more than it does. However, the missing max_entries explanation and lack of usage guidance make the description only partially complete for a tool with three parameters and zero schema descriptions.

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, so the description must compensate. It explains directory and pattern meaningfully, but completely omits max_entries. This leaves one of three parameters undocumented, a clear gap in the description's ability to compensate for the missing 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 'List files in a work directory' with a specific verb and resource. This distinguishes it from sibling tools like read_file (which reads file content) and list_jobs (which lists jobs). The scope is well-defined and unambiguous.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or contrast with sibling tools like read_file or list_jobs. The parameter explanations are more about syntax than usage 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 behavioral disclosure burden. It discloses the return format (list of job dicts with specific keys), the max history_days value, and the filter behavior. It does not mention potential edge cases or permissions, but as a read-only listing tool, the core side-effect-free nature is clear.

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 and front-loaded: one clear purpose sentence followed by parameter and return information. Every sentence provides necessary information with no filler.

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 list tool, the description is nearly complete: it covers scope, parameters, and return keys. It does not mention pagination or error behavior, but the output schema likely covers return details. The only minor gap is not specifying whether the list is paginated or sorted.

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 fully explains both parameters: history_days (include completed jobs from past N days, max 90) and rscgrp (filter by resource group name). This fully compensates for the schema's lack of 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 starts with a specific action and resource: 'List jobs for the current user.' This clearly distinguishes from sibling tools such as get_job_status (single job) or list_files, and it adds scope ('current user' and filter parameters).

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 context on what parameters affect the result (history_days, rscgrp), but it does not explicitly state when to use this tool over siblings like get_job_status or read_job_output. Usage is implied by the listing action, but no exclusions or alternatives are given.

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 implies a read-only operation by using 'list', but it does not state that it is read-only, nor does it mention any side effects, authentication needs, or rate limits. It provides no additional behavioral context beyond the action itself.

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, concise sentence that front-loads the action ('List all known Genkai resource groups') and includes the key output detail (type). Every word earns its place, with no wasted 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?

For a zero-parameter list tool with an output schema, the description is sufficient: it states the scope ('all known') and the output attribute (type). The output schema likely documents the return structure, so the description does not need to elaborate further. It is complete for its simplicity.

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

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

The tool has zero parameters, and the schema description coverage is 100% (empty schema). The description adds no parameter information, but none is needed. Given the baseline for 0 params is 4, the score reflects that the schema and description are fully aligned.

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 lists all known Genkai resource groups and their type (cpu/gpu/gpu_mig). The verb 'list' and resource 'resource groups' are specific. However, it doesn't differentiate from the sibling tool 'get_resource_groups', so it lacks explicit sibling distinction.

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 gives no guidance on when to use this tool versus alternatives like 'get_resource_groups'. There is no mention of prerequisites, context, or exclusions. The usage context is implied (discovery of available resource groups) but not articulated.

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 transparency burden. It discloses the access restriction (only work_dir), and the return fields including truncation flag. It omits error handling and encoding details, but for a read operation this is reasonably 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 three short, front-loaded sentences with no wasted words. Every sentence adds value: purpose, access scope, and return shape.

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?

Even though an output schema exists, the description explains return fields and access limits, which is helpful. It does not cover edge cases like file-not-found or binary files, but for a simple read_file tool the provided context is 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 description coverage is 0%, so the description must explain parameters. It partially clarifies file_path via the work_dir rule but never mentions max_bytes or how it relates to truncation. The return field 'truncated' indirectly hints, but it is not explicit enough.

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 uses a specific verb ('Read') and resource ('text file from the Genkai filesystem'), and adds scope ('Only files within work_dir are accessible'). This clearly distinguishes it from siblings like list_files and read_job_output.

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 reading text files within work_dir but does not explicitly state when to use this tool over alternatives (e.g., read_job_output) or provide exclusion criteria. The work_dir constraint offers context but no explicit guidance.

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

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

With no annotations, the description carries the burden but only partially. It discloses that it searches by PJM naming patterns and returns {content, truncated, path}, but omits important behaviors such as what happens on missing files, how max_bytes affects truncation, and how work_dir influences the search.

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 compact and front-loaded: purpose, search patterns, and return shape. Every sentence provides useful information with no redundancy.

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

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

For a moderately complex tool with 5 parameters and no annotations, the description covers the main purpose and search logic but leaves gaps around work_dir scope and truncation behavior. It is adequate for basic selection but not fully complete for confident invocation in edge 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?

Schema description coverage is 0%, so the description must compensate. It explains job_id and job_name through filename patterns and file_type through .out/.err, but work_dir and max_bytes semantics are not clarified beyond the mention of 'truncated' in the result object.

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 reads stdout or stderr output files of a completed job, with a specific verb and resource. The naming patterns further distinguish it from generic file-read sibling tools like read_file and list_files.

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 specifies use for completed jobs and shows the exact filename patterns searched, giving clear context for when to invoke. However, it does not explicitly mention alternatives or when not to use it, though sibling differentiation is strongly implied.

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 transparency burden. It discloses a non-obvious behavior: resource directives in the script override parameters, and parameters are ignored when #PJM directives exist. It also specifies the return type. It does not cover side effects like resource consumption, but the disclosure is solid.

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 tight sentences plus a return-type line. It front-loads the purpose, gives the critical precedence note, and stops. Every sentence earns its place with no redundancy.

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

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

Given the tool's complexity (8 parameters), the description provides the essential behavioral context and return format. The output schema exists, so return values are already structured. The main gap is lack of per-parameter details, but the precedence note is a critical piece that rounds out the overall picture.

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 the description must compensate. It explains the key parameter `script_content` and the general relationship between parameters and script directives, but it does not define individual parameters like `elapse` or `rscgrp`. The parameter names are somewhat self-explanatory, but the description only partially fills the gap.

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 action ('Submit a batch job'), the specific target ('TCS/PJM scheduler on Genkai'), and is distinct from all sibling tools. It uses a specific verb+resource pattern that leaves no 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?

Provides explicit usage context: 'Provide the full job script content' and states that script directives take precedence over parameters. However, it does not mention alternative tools like 'generate_job_template', so it lacks a direct when-to-use vs. alternatives comparison.

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