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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states that only loaded, visible cards are included and that unloaded pages are excluded, setting accurate expectations about the tool's limited scope. It does not discuss side effects, but this appears to be a read-only listing 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?

Two short sentences with no filler. The main purpose is front-loaded, and the important limitation is stated separately. Every clause earns its place.

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

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

For a simple single-parameter listing tool, the description is reasonably complete. It states what is listed and what is excluded, though it does not describe the return structure or how to find the job_id. Given the low complexity and absence of an output schema, this is a minor gap.

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

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

Schema description coverage is 0%, so the description must add meaning to the lone 'job_id' parameter. Saying 'on this job page' implies that job_id identifies the relevant job page, but the description does not explain how to obtain or format the job_id beyond what the parameter name suggests.

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 and resource: 'List currently loaded visible asset cards and thumbnail identities'. It also clarifies scope with 'on this job page' and differentiates itself from broader listing tools by noting it does not enumerate unloaded pages.

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 when to use this tool: when you need only currently loaded visible asset cards and thumbnails. The explicit exclusion of unloaded pages provides clear context, though it does not name alternative sibling tools or state 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.

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

Annotations are absent, so the description carries the full burden. It indicates a create/write operation but does not disclose side effects, whether files are modified, permissions required, idempotency, or what 'background' means.

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 front-loaded sentence with no filler, and it includes key formatting constraints. It is concise, though it trades away necessary usage and behavioral detail.

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 no output schema and no annotations, the description omits expected result, side effects, and workflow context. An agent cannot tell what happens after the script is created or how `job_id` drives the 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?

Schema description coverage is 0%, and the description never mentions `job_id` or explains how it relates to the created script. The parameter title is self-explanatory at a superficial level, but the description adds no semantic value and fails to compensate for the low schema coverage.

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

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

The description uses a specific verb and resource: it creates a 'separate background Blender import script' with concrete constraints ('metres, normalized height and grounded origin'). It is clear about the output artifact, but it does not differentiate this from close siblings in the pipeline, and the word 'background' is ambiguous.

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 explicit guidance on when to choose this tool over siblings such as workbench_prepare, workbench_submit, or workbench_ingest. No prerequisites, workflow position, or exclusions are mentioned; only the action itself is stated.

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 burden of behavioral disclosure. 'Read' signals a non-mutating operation and 'visible job page' clarifies what is observed, but it does not explain the output format, whether a browser session must be active, or any other behavioral nuances.

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?

A single sentence with no filler, front-loading the main verb and resource, and ending with the use case. Every word contributes to the agent's understanding.

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 read-only tool with one optional parameter, the description is mostly adequate. However, it does not explain what the return value looks like (no output schema exists) or mention any prerequisite like having a browser started, which could matter given the browser_* sibling tools.

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 a single optional job_id with 0% description coverage. The description's mention of 'job page or default page' implies that job_id selects a specific job page while omission uses the default page, adding meaning beyond the schema. However, this relationship is not stated explicitly.

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 states a specific action ('Read') and a resource ('the visible job page or default page'), with a clear diagnostic purpose ('for diagnosing a changed UI'). It is distinct from sibling browser tools like start, run, and result, though it does not explicitly name them.

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

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

The phrase 'for diagnosing a changed UI' provides a clear context for when to use the tool, but it does not mention alternatives or state when not to use it. The usage guidance is implied rather than explicit relative to the sibling 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?

There are no annotations, so the description carries the full burden. It discloses that this is a retrieval operation and warns against repeated page inspection, which is useful behavioral context. It does not mention error behavior, persistence, or side effects, but for a simple read operation this is acceptable.

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 short sentences with no filler. The core action is front-loaded and the caution about watches is placed second, making the most important instruction immediately visible.

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 has only one parameter and no output schema, so the description does not need to explain complex return values. However, it omits where request_id comes from and what shape the result takes, leaving minor gaps for an agent that must invoke the tool correctly in a larger workflow.

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 explain what request_id means, where it comes from, or how it relates to other workbench calls. The parameter name is self-explanatory at a basic level, but the tool description adds no semantic 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 states a specific action ('Retrieve') and a specific object ('one local request result'), making the core purpose clear. It does not explicitly contrast with sibling tools like workbench_get or workbench_browser_inspect, but the wording is specific enough to distinguish intent.

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 practical usage direction: use watches for generation progress and do not repeatedly inspect the page with this tool. It implies an alternative behavior but does not name the exact sibling tool, so it stops short of fully explicit routing.

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 must disclose behavior itself. It does mention that the operation consumes web quota and that submit=True starts local monitoring and automatic download, which is useful. However, it leaves the submit=False behavior implicit, does not state whether the operation is destructive or creates persistent state, and gives no blocking or timeout 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?

The description is two sentences with no wasted words. It front-loads the primary action and then explains the conditional submit behavior and the quota cost, which is optimally compact for the information provided.

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 core behavior for a two-parameter tool is present, but there is no mention of return values or result format, no prerequisites, and no guidance on how this relates to the many sibling tools. Given no annotations and no output schema, an agent would still have open questions about what happens after invocation and how to combine this with other workbench steps.

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 submit=True well: generates once, starts local monitoring, and auto-downloads. job_id is only surfaced as 'Job Id' in the schema, and the description does not clarify what kind of job reference is valid or whether the job must already be prepared.

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 uploads and configures the full job in one local execution, which identifies a specific combined action. The submit flag adds detail about generate/monitor/download behavior. It does not explicitly name sibling differences, but the phrase 'in one local execution' hints at being a consolidated alternative to multi-step workflows.

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?

Usage context is implied: use this tool for a one-shot full job execution, with submit=True enabling generation, monitoring, and automatic download. However, it never says when to use this instead of related tools such as workbench_submit, workbench_browser_start, or a prepare-then-run sequence, and it omits 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?

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal two important behaviors: the browser session is persistent and the tool reuses an existing official web login rather than prompting for new credentials. It does not mention side effects, failure modes, or what happens on reconnect versus fresh start, but the core behavior 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 two short sentences with no filler. The primary action is front-loaded and the authentication detail is concise and relevant. Every word earns its place.

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

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

Given zero parameters and the straightforward nature of a start/reconnect operation, the description provides enough context for an agent to understand the tool's role. Mentioning persistence and existing login is valuable. It could be slightly stronger by noting the relationship to browser_run or browser_inspect, but this is a minor gap for such a simple tool.

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

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

The tool has zero parameters, so there is no parameter detail for the description to add. A baseline of 4 is appropriate because there is nothing the description must clarify about arguments.

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 identifies the action ('Start/reconnect') and the resource ('persistent local browser'), making the tool's purpose immediately understandable. It is not a tautology and has enough specificity to distinguish it from generic browser operations, though it does not explicitly contrast with sibling tools.

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

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

The phrase 'Start/reconnect' implies when the tool should be used: when the persistent browser session needs to be initiated or resumed. The note about using its 'existing official web login' gives useful context about authentication expectations. However, it does not explicitly say when to use this tool versus siblings like workbench_browser_run or workbench_browser_inspect.

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 behavioral disclosure burden. It meaningfully discloses that the catalog is observed, includes tested status, and documents current limitations, which helps set expectations about reliability and completeness. It does not state whether the tool has side effects, but for a zero-parameter capabilities tool 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 extremely concise, front-loaded with the primary content, and every phrase adds value. 'Excludes world generation' is a useful scoping exclusion in a single short sentence. No filler or redundancy is present.

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 introspection tool with no output schema, the description is largely complete: it tells the agent what the tool provides and what it excludes. It could be slightly more helpful by indicating a prototypical use case, such as checking workbench capabilities before invoking other workbench tools, but it is not critically 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 tool has no parameters and an empty input schema, so the baseline is 4. The description adds context about what will be returned rather than parameter details, which is appropriate here since there are no parameters to document.

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 conveys that the tool returns a catalog of observed features, inputs, tested status, and limitations. It is clearly a capabilities/introspection tool rather than an operation tool, and it explicitly excludes world generation, which narrows its scope. However, it lacks a direct verb like 'Lists' or 'Reports' and does not differentiate itself from sibling tools such as workbench_status or workbench_list.

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 states the content of the tool but gives no guidance on when to use it versus alternatives. There is no mention of when to consult capabilities versus workbench_doctor, workbench_status, or workbench_list, and no explicit conditions or exclusions beyond world generation.

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 behavioral burden. 'Inspect' implies a read-only diagnostic operation and the listed targets add useful context, but the description does not disclose side effects, return format, or whether any monitoring state is refreshed as part of the inspection.

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, direct sentence with no filler. It front-loads the verb and clearly enumerates the three inspected areas, making every word useful.

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 diagnostic tool, the description is mostly self-sufficient and clearly enumerates the scope of inspection. However, with no output schema and no usage guidance, an agent still lacks information about what result to expect and when this tool is the right choice among the many siblings.

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 coverage is vacuously 100%, so there are no parameter semantics to clarify. The description appropriately focuses on what the tool inspects rather than any inputs.

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 names a specific verb, 'Inspect', and concrete resources: local runtime, worker heartbeat, and persisted monitoring state. It is clear about what the tool examines, though it does not explicitly distinguish itself from sibling diagnostic tools like workbench_status or workbench_watch.

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 the many sibling tools. The description states what it inspects but not the conditions or context in which an agent should choose workbench_doctor over alternatives.

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

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

With no annotations, the description carries the full burden of disclosing behavior. It does disclose the multi-step behavior: downloading via official UI, validating, archiving, and never generating again. However, it omits details like authentication requirements, what 'archive' does to data, and whether the operation has side effects beyond the download.

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, approximately two short sentences, and every phrase adds information: the selection criterion, the download mode, validation, archiving, and the non-generation guarantee. There is no redundant fluff.

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 description provides a high-level workflow but is incomplete for actual invocation. It lacks any explanation of the input parameters, expected output, or operational prerequisites beyond 'completed asset.' With no output schema and no annotations, this is a material gap.

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

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

Schema description coverage is 0%, so the description must compensate by explaining the parameters, but it never mentions job_id or format_name. 'Matching completed asset' vaguely implies job_id, but format_name is completely unaddressed. An agent cannot reliably know how to set format_name from this 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 gives a specific workflow: select a completed asset, download it, validate, and archive. It clearly describes the resource and action, and the line 'Never generates again' helps distinguish this download tool from generation-oriented siblings, even though no sibling is explicitly named.

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 phrase 'Select the matching completed asset' provides clear context that this tool should only be used when a completed asset already exists. 'Never generates again' is an explicit exclusion, telling the agent this tool is not for generation. It does not name alternative tools, but the usage boundary is reasonably 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 behavioral transparency burden. It clearly signals a read-only operation ('Read') and explicitly disclaims side-effectful browser activity ('no browser calls'). It could add more about authentication or output behavior, but for a simple read 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?

The description is a single front-loaded sentence with no filler. It states the core operation first, then the key scoping constraint ('no browser calls'), earning every word.

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

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

For a tool with one required string parameter, no output schema, and no annotations, the description covers the core purpose, return content, and a key behavioral boundary. It is slightly thin on parameter provenance and selection guidance, but overall an agent can invoke this tool correctly with the information provided.

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 the job_id parameter. Saying 'Read one job' conveys that job_id identifies a single job, but it does not explain the ID's format, where to obtain it, or how it relates to sibling tools like workbench_list. The compensation is minimal.

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 a clear resource ('one job'), and further specifies the data returned: input hashes and state history. It also explicitly distinguishes itself from browser-oriented siblings with 'no browser calls', so an agent can select it confidently.

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 this tool is for reading a single job's details, and 'no browser calls' hints it is not for browser automation. However, it does not explicitly name alternatives or state when to use this tool versus workbench_list, workbench_status, or workbench_watch.

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 of behavioral disclosure. It reveals that the tool validates and archives, but it does not describe side effects, whether archiving is irreversible, what validation checks occur, or what happens on failure. This is a significant gap for a tool that likely moves or stores files.

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, tightly worded sentence. Every word contributes meaning, including 'manually' and 'confirmed successful,' which set scope. There is no fluff or repetition.

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

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

For a tool with no annotations, no output schema, and no parameter documentation, this description is too thin for confident invocation. An agent would still need to infer how to supply the file, what validation means in this context, and what the archive step does to the artifact.

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 define either parameter. It implies that 'downloaded_file' is the manually downloaded artifact and 'job_id' refers to the confirmed successful job, but it omits critical details like file path format, accepted values, or expected relationship between the two parameters.

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

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

The description states specific actions ('Validate/archive') on a clear resource ('a manually downloaded artifact') and an explicit condition ('confirmed successful job'). This makes it distinguishable from sibling tools like workbench_download, though no sibling is named directly.

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 phrase 'manually downloaded artifact for a confirmed successful job' gives a clear context for when to use this tool. However, it does not explicitly explain when not to use it or point to an alternative tool, leaving some routing decisions to the agent.

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?

There are no annotations, so the description carries the behavioral burden. 'Read durable local jobs; no browser calls' conveys that this is a read-only, non-browser operation, which is helpful. It does not mention result shape, ordering, pagination, or error behavior, so transparency is adequate but limited.

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: a single sentence with two clear clauses. Every word contributes either to the resource being read or to the key exclusion of browser calls, 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 zero-parameter, no-output-schema tool, the description covers the essential purpose and the main behavioral constraint. It could say more about what the returned data contains, but 'Read durable local jobs' is enough to guide invocation correctly in most 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 tool has zero parameters, so the baseline is 4. There is nothing for the description to add beyond what the empty input schema already shows, and no parameter meaning is left undocumented.

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

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

The description uses a specific verb 'Read' with a clear resource, 'durable local jobs,' and adds the distinguishing trait 'no browser calls.' This separates it from browser-related siblings, though it does not explicitly differentiate it from reading/status tools like workbench_get or workbench_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?

'No browser calls' implies this is the non-browser route for reading local jobs, which is useful context. However, it does not name alternatives or state when to prefer this over workbench_get, workbench_status, or workbench_watches, leaving usage mostly 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 full burden. It usefully discloses non-behaviors ('does not submit', 'does not consume quota') and a constraint ('including front'). Yet it does not clarify potential side effects of copy/deduplicate, required state, permissions, or failure modes.

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 compact, with the core behavior and the key constraint front-loaded in the first sentence. The second sentence adds an important distinguishing fact. No filler or redundancy exists.

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

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

For a tool with 5 parameters, a nested views object, no output schema, and no annotations, this description is too sparse. It addresses only the views count and the submit/quota behavior, leaving the agent to guess about parameter formats, defaults, return values, and overall invocation semantics.

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 parameters. It only adds meaning for 'views' by specifying a count range of 3..8 and requiring 'front'. The other parameters (name, height_m, revision, face_count) remain unexplained, leaving the agent without enough semantic information to set them correctly.

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 states the core operation ('Validate/copy/deduplicate') on a specific resource ('3..8 views including front') and clarifies it does not submit or consume quota. This is sufficiently specific to differentiate it from submission-style tools, though the compound verb list makes the exact primary action slightly ambiguous.

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 phrase 'Does not submit or consume quota' implies this is a pre-submission preparation step, which gives some contextual guidance. However, it does not explicitly name alternatives, state when to choose this over workbench_prepare_feature, or describe 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?

There are no annotations, so the description must carry the full burden of behavioral disclosure. It reveals only that the tool validates and 'preserves local inputs,' but does not explain what preservation means, whether there are side effects, what happens on failure, or what the output looks like.

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 short and front-loads the core action in the first sentence. The second sentence points to external references, which is helpful but slightly reduces self-containedness. Overall, no words are wasted.

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 no annotations, no output schema, and a free-form spec object, the description leaves too much unspecified. The tool cannot be correctly invoked based solely on this description, and it defers critical schema details to the README and capabilities rather than including them.

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 sole parameter 'spec' is an open object with additionalProperties true. The description only labels it as a feature specification, without providing structure, expected fields, or examples, so it does not compensate for the schema 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 uses a specific verb ('validate') and identifies a clear resource ('feature specification'), and also mentions the additional behavior of preserving local inputs. However, it does not differentiate this tool from the similarly named sibling workbench_prepare, so it stops short of a 5.

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 this tool is used when you need to validate a feature specification, and it directs the agent to capabilities and README for schemas. But it provides no explicit when-to-use versus alternatives such as workbench_prepare, and no exclusion criteria or prerequisites are stated.

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

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

With no annotations, the description carries full behavioral burden. It discloses that the tool 'never generates,' but it does not explain side effects of rebinding, whether it mutates state, requires permissions, or can be undone. For a recovery/mutation tool, this is a significant gap.

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

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

Three short sentences, each carrying meaningful information, with the primary purpose front-loaded. The word 'Explicitly' is somewhat redundant, but overall the description is efficiently written.

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 3 required parameters, no output schema, no annotations, and 18 siblings, the description is too sparse. It lacks definitions for 'evidence' and 'job_id,' omits return-value or side-effect information, and does not differentiate itself from sibling tools beyond a vague 'never generates.'

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 only clarifies 'thumbnail' ('must identify the one selected card'); 'job_id' is self-explanatory by name but undocumented, and 'evidence' is entirely unexplained. The description fails to adequately define two of the three required parameters.

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

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

The description states a specific action ('rebind an interrupted task') and adds a clear constraint ('only after reviewing its matching completed asset'). The phrase 'Never generates' helps distinguish it from generation-focused siblings, though 'rebind' remains domain-specific jargon.

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 provides a clear precondition (use only after reviewing the completed asset) and implies it's for interrupted tasks, but it does not explicitly name alternatives or enumerate when-not-to-use conditions. 'Never generates' is a behavioral constraint rather than usage guidance.

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

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

With no annotations, the description carries the full behavioral burden. It does disclose a read/refresh dual-mode and mentions 'enqueue a fresh check', which hints at side effects, but it does not explain consequences, whether the check is asynchronous, what local state means, or any failure behavior.

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

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

The description is a single short sentence with the core behavior front-loaded. No filler or redundancy, though the phrase 'exactly bound' could be clearer without adding 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?

For a tool with no annotations, no output schema, and 0% schema coverage, this description is too thin. It leaves unclear what the returned status looks like, what 'exactly bound' means, what triggers a refresh, and how job_id relates to the asset.

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, but it does not explicitly explain either parameter. 'Fresh check' loosely maps to the refresh flag, and 'exactly bound web asset' hints at job_id, but the mapping is implicit and incomplete.

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 states a specific action ('Read local state or enqueue a fresh check') for a resource ('web asset'), so it is not a tautology. However, 'exactly bound web asset' is vague jargon, and the tool's purpose is not clearly distinguished from siblings like workbench_watch or workbench_get.

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 any of the many siblings. The dual-mode behavior implies some usage context, but no conditions, exclusions, or alternatives are stated.

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 transparency burden. It discloses meaningful behavioral traits: the action is one-time, requires user authorization, and may consume web quota. It stops short of describing post-submission state or failure behavior, so it does not reach a 5.

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 tight sentences front-load the core action and state requirement, then append the authorization and quota caveats. Every word adds operational guidance with no redundancy or restatement of schema fields.

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 one-parameter submit action with no output schema, the description covers the essential operational context: what to submit, when it is allowed, the one-time constraint, and quota consequence. Some detail about what happens after submission is missing, but the simple scope keeps this gap minor.

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

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

The schema has 0% description coverage for job_id, and the description does not explicitly mention job_id. However, describing the target as 'an already prepared READY form' implies job_id identifies that prepared form, providing minimal semantic context without fully explaining the parameter.

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 ('Submit') with a clear object ('an already prepared READY form'), establishing the exact action and required state. The phrase 'already prepared READY' differentiates it from sibling preparation tools like workbench_prepare.

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 clearly signals the tool is for the post-preparation step by requiring a READY form, and it adds explicit constraints: exactly once, user authorization required, and possible web quota consumption. It does not explicitly name alternative tools, but the workflow 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, the description carries the full burden and does disclose two non-obvious behavioral traits: monitoring checks run in the worker without repeated model calls, and stopping monitoring does not cancel generation. It could add more about response behavior or side effects, but the key operational and safety-relevant behaviors are surfaced.

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 sentences with no filler, front-loaded with the purpose, and every sentence adds distinct behavioral or contextual information. It is appropriately sized for the tool's complexity.

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

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

With five parameters and no output schema, the description is not complete enough for an agent to configure the tool confidently. It omits parameter semantics such as interval units, format_name values, and auto_download behavior, and says nothing about the return value or how existing watches are affected.

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 the five parameters, but it does not explain job_id, enabled, interval, format_name, or auto_download. Phrases like 'stopping monitoring' weakly map to enabled, but no parameter receives meaningful semantic clarification.

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 and resource ('Configure persistent local task monitoring') and makes the tool's role clear compared to one-time status checks or listing watches. It does not explicitly name a sibling tool, but the wording distinguishes it from workbench_status and workbench_watches well enough.

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 clear context: this is for persistent, low-overhead monitoring because checks happen in the worker without repeated model calls. It also warns that disabling monitoring is not a cancellation action, which is important guidance for when to stop using it. It does not explicitly enumerate alternatives or exclusions, so it is not a 5.

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 behavioral disclosure burden. It communicates a read-only operation from disk and enumerates the returned data categories, but does not mention staleness, scope (all watches vs. a single watch), or any other behavioral caveats.

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, tightly written sentence that leads with the action and lists the relevant data contents. There is no filler or redundant 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 no-parameter, no-output-schema tool, the description adequately conveys what will be read and from where. It could be more explicit about whether it returns all watches or a single watch, but the enumerated fields give an agent enough context to invoke it 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 tool has zero parameters, so the schema fully covers parameter semantics by having an empty properties object. The description does not need to add parameter detail, matching the baseline of 4 for parameterless tools.

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 identifies the resource: monitor results, errors, next check times, and attention flags from disk. This clearly distinguishes it from an abstract or tautological definition, though it does not explicitly contrast it with the sibling workbench_watch.

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 about when to use this tool versus alternatives like workbench_watch, workbench_status, or workbench_get. The agent must infer usage from the name and description without any stated selection criteria.

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