AImeistrO

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

With no annotations, the description carries the full behavioral burden. It helpfully discloses the autonomous Value Loop steps and the returned fields (providers, economics, provenance), but says nothing about blocking vs. async behavior, whether the AMC budget is actually charged, permission needs, or rate/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?

Two sentences, both earning their place: the first states the action, the second enumerates the pipeline and the returned payload. Front-loaded with the core action and 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 6-required-param mutation tool with no output schema and no annotations, the description compensates well by enumerating returned fields in place of an output schema. It still omits synchronous/asynchronous behavior and budget-charging semantics, which matter for a paid generation call.

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

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

Schema description coverage is 100%, so bpm, key, bars, type, style and budget are already documented in the schema. The description adds no parameter-level meaning beyond what the schema provides, making the baseline 3 appropriate.

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

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

The description names a specific verb and resource ('Submit a music production request to AImeistrO') and then describes the internal pipeline (bidding, MIDI generation, QC) plus the return payload. This clearly distinguishes it from the retrieval siblings get_job and get_artifact, though it never names them explicitly.

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 is only implied: the stated return of 'job status' and 'artifact reference' hints that get_job and get_artifact are the follow-up tools, but no when/when-not condition or alternative is stated. An agent must infer the workflow from the sibling names.

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 present, the description carries the full burden, and it does disclose the return format (base64-encoded MIDI data with metadata) and the 'completed' precondition. It omits other behavioral details such as behavior on incomplete jobs, permission/auth needs, or payload size characteristics.

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 tightly written sentences with zero filler: the first states the action and scope, the second states the return payload. The key information is front-loaded.

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

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

For a one-parameter tool with no output schema, the description supplies the return value detail (base64 MIDI plus metadata) that would otherwise be unknown, plus the completion precondition. It is close to complete, missing only error/failure behavior for incomplete jobs.

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

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

The single job_id parameter has 100% schema description coverage including a format example (AIM-JOB-000001), so the schema does the heavy lifting. The description adds no syntax or semantic detail beyond implying the job must be completed, matching the baseline for fully documented schemas.

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 (Retrieve) and resource (raw MIDI artifact) and scopes it to a completed AImeistrO job. It does not explicitly differentiate from the sibling get_job, which also operates on a job_id, leaving some ambiguity about which to call for artifact vs. job metadata.

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 a completed AImeistrO job' implies the precondition that the job must have finished, which is useful routing context. However, it never explicitly states when to use this over get_job or what to do if the job is still running, so usage is only 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?

No annotations are provided, so the description carries the full disclosure burden. It implies a read but says nothing about blocking vs. polling behavior, what happens when the job is not found or still running, or what 'status' values exist. For a job-status tool with zero annotation coverage this is a real 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?

A single, front-loaded sentence with no filler. The action, resource, and scope are all stated in the opening clause, which is exactly what an agent scanning for the right tool needs.

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, so the description must carry the return-value burden; 'status and result' is only a shorthand sketch and does not indicate the shape of a completed result versus an in-progress status. Combined with missing usage and behavioral context, the definition is minimally adequate for a one-parameter read 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?

There is a single parameter at 100% schema description coverage, and the schema already documents the job_id format with an example (AIM-JOB-000001). The description's 'by its job ID' adds no syntax or constraint beyond the schema, so the baseline 3 applies.

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

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

States a specific verb (Retrieve) and resource (AImeistrO job) plus the scope ('status and result ... by its job ID'), so an agent knows exactly what comes back. It is clear, but it never names or contrasts the siblings create_music and get_artifact, leaving differentiation implicit.

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 offers no when-to-use guidance, no condition for polling, and no mention of the alternatives (e.g. get_artifact for the produced file). The workflow context — call after a job is created, when to stop polling — is left entirely to inference.

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