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 effectively communicates that cancellation is not immediate and that the job status changes only after worker confirmation, which is a key non-obvious behavioral trait. It does not cover error cases or idempotency, but the most important caveat is present.

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, lean sentence that front-loads the action and immediately follows it with the critical asynchronous caveat. Every word adds value, and there is no redundant or filler 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 one-parameter tool with no output schema and no annotations, the description covers the essential invocation context and the crucial post-condition behavior. It lacks return value details and edge-case behavior, but the simplicity of the tool and the explicit async warning make it reasonably complete for an agent to call 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?

Schema description coverage is 0%, and the description does not explicitly define job_id or its format. The parameter name and title are self-explanatory, and the description loosely implies that job_id identifies the job to cancel, but the description does not compensate for the missing schema 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 action ('Request cancellation') and the async nature of the operation ('status changes only when confirmed by the worker'). While it does not explicitly mention 'job', the tool name and job_id parameter make the resource unambiguous. It distinguishes itself from read-only sibling tools by describing a cancellation action.

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

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

No guidance is given on when to use cancel_job versus alternatives, nor are there any prerequisites or exclusions. The description implies it should be used when a previously submitted job needs cancellation, but this is left to inference rather than 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 burden of disclosing behavior. It usefully reveals that the tool verifies the artifact hash, returns a local path, and only returns content when explicitly requested and bounded. However, it does not clarify what happens on hash mismatch, how 'bounded' is enforced, or whether network/IO side effects occur.

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 dense sentence with no fluff, and the primary purpose is front-loaded. The second clause is terse and somewhat ambiguous, but it still conveys the key content-related constraint without wasted words.

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

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

For a tool with no annotations, no output schema, and zero parameter descriptions, the description is too sparse. It gives the return type (local path) and a hint about content, but it omits selection criteria, artifact identification semantics, failure behavior, and precise limits, leaving the agent to infer too much.

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 parameter meaning. It adds some meaning for content and max_bytes ('content requires explicit true and is bounded'), but it does not explain how job_id and name identify the artifact, nor what units or limits max_bytes uses.

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 identifies a specific action—'Verify artifact hash and return its local path'—and a clear resource (artifact). It stops short of explicitly naming a sibling alternative like list_artifacts, but the verify-and-return-path wording differentiates it from listing operations.

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

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

No guidance is given about when to use fetch_artifact versus list_artifacts or other job-related tools. The only usage hint is that content requires explicit true and is bounded, which is more of a parameter behavior than tool-selection guidance.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Recover durable job state' suggests reading persistent state, but it does not clarify whether this is a pure read, whether it has any side effects, what state fields are returned, or how it behaves when the job does not exist. The term 'recover' is ambiguous about whether the tool actively restores state or simply retrieves it.

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 no filler, which is concise. However, it is more under-specified than genuinely helpful: the phrase 'Recover durable job state' is cryptic and does not clearly communicate the tool's basic function to an agent.

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-parameter tool, the description leaves important gaps: it does not explain what the returned state looks like, how to distinguish this tool from list_jobs, or what the expected behavior is for missing or invalid job_ids. The lack of any output schema makes this omission more significant.

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 one required parameter, job_id, with no description coverage (0%). The description does not mention job_id at all, nor does it explain what values are expected, how to obtain a valid job_id, or how the parameter relates to the 'durable job state' being recovered. The tool description adds no value beyond the raw schema property name and type.

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 verb ('Recover') and resource ('durable job state'), and the phrase 'across agent sessions and broker restarts' gives it a distinct scope from the sibling tools like list_jobs and get_job_logs. It does not explicitly differentiate itself from those siblings by name, but the intent is reasonably clear.

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 the tool should be used when resuming work after a session or broker restart, which provides some usage context. However, it gives no explicit guidance on when to use get_job versus list_jobs, get_job_logs, or cancel_job, and no exclusions 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 behavioral disclosure burden. It does add a non-obvious behavioral trait: logs are bounded, and offset counts backwards from the end of the available log window. However, it does not explain limits, filter behavior, output format, or failure modes, so coverage is partial.

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 very short and front-loads the bounded-logs constraint, which is efficient. However, it is so terse that it borders on under-specification for a tool with five parameters and no other documentation, so it is adequate but not exemplary.

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?

There is no output schema, no annotations, and five parameters, yet the description does not mention the required job_id, the meaning of tail, search, error_only, log content, or return behavior. 'Bounded logs' is a useful hint but far from sufficient for an agent to invoke this tool correctly in varied situations.

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. It only clarifies the semantics of offset; job_id, tail, search, and error_only are left without any added meaning. Since the schema provides only titles and types, this is a significant 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 says 'Bounded logs' and refers to a log window, so an agent can infer this tool deals with logs, but it never explicitly states the action of retrieving/getting logs for a job. It also does not differentiate itself from siblings such as get_job or list_jobs; an agent must rely on the tool name to understand the primary purpose.

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

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

No guidance is provided for when to use this tool versus get_job, list_jobs, or fetch_artifact. The phrase 'Bounded logs' hints at scoping but does not explain when this tool is appropriate, what alternatives exist, or what conditions should route an agent to another sibling.

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

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

With no annotations provided, the description carries the full burden. It clearly states a retrieval behavior ('Return'), which suggests a read-only operation, but it does not disclose pagination behavior, ordering, or any assumptions about the project parameter.

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 verb and resource. There is no filler or redundant wording.

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 output schema likely covers return-value structure, and the basic purpose is stated. However, the description is thin: it omits pagination semantics, gives no usage guidance, and relies heavily on the tool name and parameter defaults to convey context.

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

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

Schema description coverage is 0%, and the tool description only clarifies the 'project' parameter by saying 'for a project.' It adds no meaning for 'limit' or 'offset', leaving their semantics to inference from the parameter names and defaults.

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 the specific verb 'Return' and names the resource 'runs and recorded conclusions' scoped to a project. It is clear about what the tool does, but it does not explicitly differentiate it from sibling tools like list_jobs or list_ready_results.

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 such as get_job, list_jobs, or list_ready_results. There are no exclusions, prerequisites, or alternative conditions mentioned.

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 behavioral burden. It clearly indicates that the tool returns metadata rather than content, implying a read-only listing. It does not disclose output format, failure behavior, or side effects, but for a simple list operation this is minimally 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?

The description is a single, compact sentence with no filler. It front-loads the return values and adds the useful 'before reading content' qualifier without unnecessary words.

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

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

For a one-parameter metadata-list tool, the description covers what is returned but omits job scoping, output shape, and potential limitations. It is adequate for a simple call but leaves the agent to rely on the schema for parameter 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 parameter meaning, but it never mentions the required job_id parameter or explains that artifacts are scoped to a specific job. The agent is left to infer how job_id relates to the returned paths, sizes, and hashes.

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 ('Return') on the artifacts resource and lists the exact metadata returned: canonical paths, sizes, and hashes. It does not explicitly name sibling alternatives, but 'before reading content' hints at the distinction from fetch_artifact.

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 'before reading content' implies when to use this tool and suggests it should precede content-reading operations. However, it does not explicitly say when not to use it or name alternative tools such as fetch_artifact.

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 it offers only two behavioral hints: the operation is a read ('List') and results are paginated. It does not explain what qualifies a job as 'persistent', whether results are ordered, or how filters behave. The unexplained 'persistent' qualifier raises more questions than the description answers.

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?

One sentence of five words with no filler: the verb, resource, and pagination mechanism are all present. It borders on under-specification by omitting filter semantics, but as written it is genuinely tight and 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?

The output schema covers return shape, but the description leaves three gaps for a tool with no annotations: 'persistent' is undefined, status/project filters have no semantics (0% schema coverage), and there is no routing guidance among 12 siblings. An agent can invoke it safely with defaults but cannot use it correctly for filtered lookups.

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 was expected to compensate, but it covers only pagination (which gives limit/offset meaning) and says nothing about status or project. Valid status values, whether filters are exact-match, and how filters combine with pagination are all unexplained. With 0% coverage, the description needed to address every parameter and did not.

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-resource pair ('List persistent jobs') and names the pagination mode, which distinguishes the tool from single-item siblings like get_job and non-job resources like list_artifacts. However, it does not explicitly differentiate from the overlapping-sounding list_ready_results or get_project_runs, and the qualifier 'persistent' is left undefined.

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 when-to-use guidance or alternative routing is given. The description names none of the 12 siblings and states no conditions, prerequisites, or exclusions, so the only usage signal is the implied action of listing. An agent cannot tell from the description whether list_jobs or list_ready_results is the right entry point for a given request.

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. It does convey that only finalized/completed results are returned ('finalized results') and that it is a read-style discovery operation, but it does not mention side effects, permissions, pagination behavior, or time-based scoping beyond 'earlier sessions'.

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 purpose first and then adds a practical usage hint. 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?

An output schema exists, so return values are presumably documented elsewhere. However, the description does not mention pagination, filtering behavior, or that all parameters are optional, and with no annotations the safety profile is unknown. For a simple list tool with three optional parameters, this is adequate but has clear gaps.

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

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

Schema description coverage is 0%, so the description must compensate by explaining the parameters. It does not mention limit, offset, or project at all. While the parameter names are somewhat self-explanatory, the description adds no meaning beyond the schema's titles and defaults, leaving the agent to infer semantics.

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 clear verb 'Discover' with a specific resource 'finalized results from earlier sessions', and adds a purpose hint with 'check status before interpreting'. It does not explicitly differentiate from sibling tools because no siblings are named, but the core action and target are 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 phrase 'check status before interpreting' implies that this tool should be used as a preliminary step before analyzing results, which is a useful contextual cue. However, there is no explicit mention of when to use this tool versus alternatives, nor any exclusionary guidance.

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

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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully states that the output is normalized and excludes credential profiles, and 'List' implies a read operation. It does not mention any potential side effects or access requirements, but for a simple listing tool this is a reasonable level of disclosure.

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 constructed sentence that front-loads the core action and resource while adding the key qualifier ('without credential profiles'). 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?

For a zero-parameter listing tool with an output schema, the description is nearly complete. It explains the tool's purpose and a key behavioral boundary, and the output schema covers return values. More explicit guidance about when to choose this over sibling tools would improve completeness.

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

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

The tool has zero parameters, and the schema reflects this with an empty properties object. The baseline for zero-parameter tools is 4, and the description does not need to explain any 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 specifies a clear verb ('List'), a clear resource ('worker capabilities'), and a scope qualifier ('normalized', 'without credential profiles'). It is immediately distinguishable from the sibling tools, all of which concern jobs, artifacts, quotas, or results rather than workers.

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 the tool: when you need normalized worker capabilities and do not need credential profiles. However, it does not explicitly state alternatives or provide exclusion criteria 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 of behavior disclosure. The verb 'Show' implies a non-mutating read, but the description does not state whether this is read-only, how the counts are scoped, or what the response format 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 a single sentence with no filler and gets straight to the point. It is appropriately short for a parameterless tool, though 'separately' could be clearer.

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 zero parameters, no output schema, and no annotations, the definition is minimal but adequate for a basic overview. It would benefit from a note on when to prefer this over list_workers or list_jobs, and from clarifying what 'durable job counts' means in practice.

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 description has no parameter semantics to add. The baseline for zero-parameter tools is appropriate here.

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 ('Show') and names the core output concepts ('worker capacities', 'durable job counts'). It implies an aggregated overview distinct from the sibling listing tools, though the word 'separately' adds slight 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?

No guidance is given about when to use this tool versus alternatives like list_workers or list_jobs. There is no explicit use case, prerequisite, or distinction from 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?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It implies a write operation ('Attach') but does not state whether this creates, updates, or mutates anything, what side effects occur, whether it is destructive, or what the return behavior is. The phrase 'immutable infrastructure artifacts' hints at separation but does not explain actual tool 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 short, but brevity is not conciseness when it delivers almost no information. The single sentence is front-loaded but vague, and every word fails to add operational value. It is under-specified rather than efficiently specified.

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

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

This tool has 5 required parameters, no output schema, no annotations, and no parameter documentation, yet the description explains none of the inputs, outcomes, or constraints. An agent has essentially no basis for correct invocation. This is completely inadequate for the tool's complexity.

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

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

Schema description coverage is 0%, and the description adds no meaning about any of the five parameters. Terms like 'scientific interpretation' might loosely map to conclusion/decision, but the description never explains job_id, baseline_metric, new_metric, decision, or conclusion. With no parameter documentation, an agent cannot reliably populate the required 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 'Attach scientific interpretation separately from immutable infrastructure artifacts' is metaphorical and vague. It does not clearly state that this tool records an experiment result, nor does it mention the metrics, decision, or conclusion that the schema shows are central. It also does not distinguish itself from siblings like list_ready_results or submit_job.

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 such as submit_job or list_ready_results. No context, prerequisites, or exclusions are provided. The only hint is that it relates to scientific interpretation, but this is not actionable.

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

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It discloses that it does not rerun the compute job (a negative constraint), but it does not explain what restarting artifact retrieval actually entails—whether it deletes previous artifacts, requires specific permissions, has side effects, or returns any result. The description gives only a minimal behavioral trait without adequate 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 a single, succinct sentence that front-loads the core action and the critical exclusion. Every word is purposeful, with no fluff or repetition. It is an excellent model of conciseness.

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

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

The tool has only one parameter and no output schema or annotations, so the description should provide enough context for safe and correct invocation. However, it lacks explanation of what 'exhausted artifact retrieval' means, what conditions warrant retrying, what the expected outcome is, or any potential failure modes. The description is too sparse to be complete for an agent that must decide when and how to use it.

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 for parameter documentation. The only parameter, job_id, is not mentioned in the description at all. While the name is self-explanatory, the description does not clarify whether job_id refers to the compute job ID or the artifact retrieval attempt ID, nor does it explain the expected format or usage. The description adds no value beyond the schema, leaving the parameter semantics poorly defined.

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: 'Restart exhausted artifact retrieval' and distinguishes it from 'never rerun the compute job.' The verb 'restart' and resource 'artifact retrieval' are specific, and the exclusion of compute jobs differentiates it from potential sibling tools like submit_job or retry compute operations. It is not a tautology and provides a clear purpose.

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

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

The description implies the usage scenario: when artifact retrieval is exhausted, this tool should be used instead of rerunning the compute job. However, it does not explicitly mention alternatives such as fetch_artifact or list_artifacts, nor does it provide conditions for when not to use the tool beyond the compute job exclusion. The guidance is implicit rather than explicit, so it meets the 'implied usage' level.

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 of behavioral disclosure. It does add a non-obvious behavioral detail: 'existing project policy controls dispatch,' implying persistence happens quickly while actual execution may be deferred or governed externally. However, it does not disclose idempotency behavior, duplicate handling, rejection conditions, or whether the returned job ID guarantees a queued/running job.

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

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

The description is a single efficient sentence with no filler, and the core purpose is front-loaded. The second clause adds a useful behavioral caveat, but it is slightly vague and could be more explicit; still, the structure is appropriately compact.

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 a complex nested JobSpec schema, an idempotency_key parameter, no annotations, and no output schema, this description is too sparse. It does not explain how dispatch policy affects the submitted job, what the returned job ID represents, how idempotency works, or what failures might occur, so the agent cannot fully predict invocation consequences.

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 adds no meaning for the two parameters, spec and idempotency_key. It does not explain that spec is the full JobSpec configuration or describe what idempotency_key is for, leaving the agent to rely only on field names, types, and defaults in the schema.

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

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

The description states a specific action ('Persist an experiment') and a concrete result ('return its job ID'), which clearly distinguishes submit_job from siblings like get_job, cancel_job, and list_jobs. The added note that project policy controls dispatch further clarifies that this is the submission entry point, not a record or retrieval operation.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites such as an existing project, valid experiment, or policy requirements. It does not name any sibling tool or exclusion condition, leaving the agent to infer usage solely from the tool 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?

Without annotations, the description must disclose behavior itself. It offers a useful semantic caveat—'unknown is not zero'—and clarifies the source is authoritative. However, it doesn't say whether sync is destructive, requires credentials, or what state is affected, so transparency is partial.

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 clauses, no filler; the action is front-loaded and the caveat is appended. 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?

For a zero-parameter tool with an output schema, little is needed to construct a valid call, and the output schema covers return values. However, the description leaves open when to call it and what 'refresh' implies for existing state, which are meaningful gaps for an agent deciding to invoke it.

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

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

The input schema has 0 parameters, so there is nothing for the description to document. Baseline 4 applies because no parameter documentation is needed.

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 ('Refresh') and resource ('authoritative provider quotas'), so an agent can understand the operation. It doesn't explicitly differentiate from siblings, but none of the siblings concern quota syncing, so no confusion arises.

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

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

No guidance on when to invoke this tool versus alternatives, or whether it should be run before other quota-dependent operations. The only contextual clue is the word 'Refresh', but the description never states when it is needed or what prerequisites exist.

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