Fireworks AI MCP by usefulapi

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

Annotations provide only a destructiveHint=true, so the description must carry most of the behavioral burden. It usefully discloses the metadata-only/additive nature and the control-plane endpoint (POST /v1/accounts/{account_id}/datasets), but it does not explain why the operation is flagged destructive (e.g., overwriting an existing datasetId) or address idempotency. Some added value, with real gaps.

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 compact sentences with the core action front-loaded and the scoping caveat attached inline. The raw endpoint path is slightly redundant implementation detail, but overall there is little waste.

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 create tool with no output schema and a low-coverage annotation set, the description covers purpose and the metadata/data split but omits what happens on a duplicate datasetId, permission or auth requirements, and any indication of the returned resource. Adequate but not complete.

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% (all 8 parameters, including the format enum and account_id override, are documented in the schema), so the schema already does the heavy lifting. The description adds no parameter-level detail, which is the expected baseline at full 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?

States a specific verb (Creates) and resource (a dataset metadata record in Fireworks) and immediately scopes the operation as metadata-only with the actual data uploaded separately. An agent can distinguish this from fireworks_get_dataset and fireworks_list_datasets without opening any schema.

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 explains what the tool does but never says when to choose it over alternatives. There is no guidance on prerequisites, no mention that a separate data-upload step must follow, and no routing to any sibling tool. Only implied usage is present.

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 already declare destructiveHint=true, and the description adds real value beyond that: it specifies the consequences (stops serving, stops billing) and identifies the underlying control-plane call. It does not state irreversibility, recovery options, or whether deletion is asynchronous.

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 that front-loads the verb and effect, with the endpoint detail relegated to the end. Every clause earns its place; nothing is padded.

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 two-parameter destructive tool with no output schema, the definition covers the essential behavioral facts. Only the irreversibility/async nature is left unstated, a minor gap given the annotation already flags destructiveness.

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 100%, so both parameters are already documented; the baseline of 3 applies. The embedded DELETE path does hint that account_id and deployment_id are resource path segments, which adds marginal meaning but no format or override behavior 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?

States a specific verb (DELETES/shuts down) and resource (a Fireworks deployment), plus the concrete effect: stops serving the model and stops billing. Clearly distinguishable from siblings like fireworks_get_deployment and fireworks_list_deployments.

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 destructive framing implies when it is appropriate, and the control-plane note gives some context, but there is no explicit when-to-use/when-not guidance or pointer to an alternative (e.g., scale-down or a non-destructive update tool). Usage must be inferred.

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 already declare readOnlyHint=true, so the safety profile is covered. The description adds useful context by identifying this as a control-plane call and giving the underlying REST route (GET /v1/accounts/{account_id}), but it says nothing about behavior when account_id is omitted (env-var fallback) or about error/permission semantics.

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, purpose front-loaded ahead of the endpoint detail. Both sentences carry information (what is returned, which API surface), though the REST route is marginal for an agent that only needs invocation semantics.

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?

A simple single-parameter read tool with no output schema, full schema coverage, and a readOnly annotation needs little more. The description's mention of returned fields (display name, state) covers the return-value question adequately, leaving only minor gaps around error cases.

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

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

Schema description coverage is 100% and the single parameter is fully documented there, including the FIREWORKS_ACCOUNT_ID override. The description adds no parameter meaning 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 (Get) and resource (Fireworks account record) and even names the fields returned (display name, state). No sibling competes for the same resource (all siblings target datasets, deployments, jobs, models, users), so differentiation is achieved implicitly by the resource name.

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 never says when to use this tool, what prerequisites exist, or what an agent should do instead when it already has account context. Usage is only inferable from the name; there is no explicit when/when-not guidance.

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

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

The readOnlyHint annotation already declares the safe-read profile, so the description's burden is lighter. It adds the control-plane route, which confirms the call is an account-scoped GET, but says nothing about failure modes (e.g. a missing dataset) and adds no other behavioral context.

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

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

Two short sentences with the purpose front-loaded and the API route as secondary detail. Nothing is redundant or padded.

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 two-parameter read-only getter with 100% schema coverage, the description covers identification and endpoint semantics adequately. It could note that the response is the dataset object, since there is no output schema, which is the only remaining 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 100%, so both parameters (account_id override, dataset_id resource segment) are already documented in the schema. The description adds only the path template echoing those same parameters, which is the baseline-3 case.

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 and resource ('Get a single dataset by id'), and the word 'single' implicitly contrasts with the sibling fireworks_list_datasets. It does not explicitly name or differentiate against that sibling, so it falls 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?

Usage is only implied: an agent infers it should call this when it already has a dataset_id, versus fireworks_list_datasets when it does not. There is no explicit when-to-use statement, prerequisite, or named alternative.

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 already declare readOnlyHint=true, so the safe read-only nature is covered. The description adds the control-plane endpoint path, which gives useful context about the underlying API, but it does not disclose auth requirements, rate limits, error behavior, or return shape.

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, front-loaded with the action and resource. Every element earns its place: the purpose and the exact REST endpoint. No filler 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 simple read-by-id tool with full schema coverage and a readOnly annotation, the description gives enough to invoke correctly. It does not describe the returned deployment object, and there is no output schema to compensate, but that is a minor gap for this level of 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 100%, so both parameters are fully documented in the schema. The description mentions 'by id' and embeds the path parameters, but adds no syntax, constraints, or meaning beyond what the schema already provides. 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 and resource: 'Get a single deployment by id.' This clearly distinguishes it from list_deployments and delete_deployment, which are the closest siblings. No ambiguity about what the tool does.

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

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

The description implies usage by saying it retrieves a single deployment by id, but it does not explicitly state when to use it versus list_deployments or how to obtain a deployment id. No exclusions or alternatives are provided.

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 already declare readOnlyHint=true, so the safety profile is covered. The description adds only the control-plane endpoint mapping, which is modest extra context; it says nothing about what the response contains, auth beyond the account id, or error behavior for a missing 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?

Two tight sentences with the core purpose front-loaded; the endpoint path is compact and informative rather than padding. Nothing is 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 simple read-only lookup with complete schema coverage and annotations carrying the safety profile, the description covers what an agent needs. The only minor gap is that no output schema exists and the description doesn't hint at the returned job shape.

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 100%, so both parameters are already documented in the schema (job_id as resource segment, account_id overriding FIREWORKS_ACCOUNT_ID). The description's 'by id' only restates job_id and adds no syntax or format detail beyond the schema, making the baseline 3 correct.

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 (Get) and resource (a single supervised fine-tuning job) with the selector (by id), which cleanly distinguishes it from the sibling list_fine_tuning_jobs. An agent can identify the tool's job without opening the schema.

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 word 'single' and 'by id' implicitly signal this is the point-lookup counterpart to list_fine_tuning_jobs, giving clear usage context. However, it never names the alternative or states when not to use this tool, so it stops short of explicit routing 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?

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds the underlying route (GET /v1/accounts/{account_id}/models/{model_id}), which hints at scoping and auth context, but says nothing about return shape or error 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 short sentences, front-loaded with the action and followed by the endpoint path. Nothing is wasted, though the endpoint string is somewhat redundant for an agent that does not need the raw route.

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 getter with a fully described two-parameter schema and an annotation covering safety, the description supplies everything needed to call it correctly. Only marginal gaps remain, such as what the response contains.

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 both model_id and account_id are already documented in the schema, including the account_id override semantics. The description adds no parameter meaning beyond that, 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 states a specific verb and resource ('Get a single model by id'), and the word 'single' cleanly separates it from the sibling fireworks_list_models. It does not name that sibling explicitly, 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?

Usage is only implied by the name and the 'by id' phrasing; there is no explicit statement of when to use this versus list_models or list_deployed_models. The 'control-plane' note gives context about the API surface but not 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?

The readOnlyHint annotation already establishes this is a safe read. The description adds the control-plane endpoint (GET /v1/accounts/{account_id}/batchInferenceJobs), which is useful context about which API surface is hit. It says nothing about pagination behavior or default page size, which is the main remaining behavioral 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?

Two short sentences, purpose front-loaded before the endpoint detail. Nothing wasted, though the endpoint string is the weakest-value content and could be trimmed.

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 read-only listing tool with 100% schema coverage and annotations covering safety, the description is close to sufficient. The one omission is how results are paginated beyond the schema's pageToken hint, which is a minor gap rather than a blocking one.

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 all three parameters (pageSize, pageToken, account_id) are fully documented in the schema. The description only implicitly reinforces account_id via the path template; baseline 3 is appropriate when the schema carries the parameter burden.

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?

Clear verb+resource: 'List batch inference jobs in the account' tells the agent exactly what it returns and the scope (account-level). It doesn't explicitly distinguish itself from siblings like fireworks_list_fine_tuning_jobs, but the resource noun is specific enough to differentiate on its own.

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, no conditions, and no alternative tools referenced. The agent gets no help deciding between this and fireworks_list_fine_tuning_jobs or fireworks_get_fine_tuning_job for job-status lookups.

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?

The readOnlyHint annotation already establishes this is a safe read operation, lowering the bar. The description adds the control-plane endpoint (GET /v1/accounts/{account_id}/datasets), which clarifies account scoping, but says nothing about pagination behavior or result limits beyond what the schema implies.

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 compact sentences, front-loaded with the action and scope, and the endpoint is appended as supporting detail. No wasted words.

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

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

For a simple read-only list tool with fully covered parameter schema and no output schema, the description covers what is needed. It omits any note on pagination semantics, but the schema's pageToken description carries that.

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 pageSize, pageToken, and account_id are already fully documented in the schema. The description adds no parameter-level detail beyond restating the account-scoped endpoint, so the baseline of 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 and resource ('List datasets in the account'), which cleanly separates it from sibling list_* tools like list_models or list_deployments. It doesn't explicitly differentiate itself from the related get_dataset or create_dataset siblings, but the purpose is 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?

There is no guidance on when to use this versus alternatives such as get_dataset (for a single dataset) or how it relates to create/delete flows. Usage is only implied by the verb 'List'.

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?

readOnlyHint=true already tells the agent this is a safe read, so the description only needs to add beyond that. It contributes the 'control-plane' framing and the concrete endpoint path, which are modestly useful, but it says nothing about pagination behavior, result size, 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?

Two compact clauses, with the core purpose front-loaded and the clarifying parenthetical immediately after. Nothing is wasted, though the endpoint path is arguably filler for an agent that cannot call URLs directly.

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-required-parameter read-only list with full schema coverage and readOnlyHint, the safety and input story is complete. However, with no output schema, the description never indicates what a listed binding contains or how nextPageToken is surfaced, leaving a modest completeness 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?

All three parameters are fully documented in the schema (pageSize max 200, pageToken as opaque cursor, account_id override), and the description adds no parameter detail at all. Baseline 3 is appropriate when schema coverage is 100%.

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 verb and resource ('List deployed models') and disambiguates with the parenthetical '(model↔deployment bindings)', which separates it from the ambiguous siblings fireworks_list_models and fireworks_list_deployments. It stops short of explicitly naming those alternatives, so it is clear but not maximally distinguishing.

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 when-to-use guidance, no condition selecting this tool over the near-identical fireworks_list_deployments or fireworks_list_models siblings, and no note on prerequisites. The endpoint path is context, not 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?

Annotations already declare readOnlyHint=true, so safety is covered. The description adds that this is a control-plane read against /v1/accounts/{account_id}/deployments, which confirms account scoping, but says nothing about pagination behavior, result size, or permissions.

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, front-loaded sentences with no filler. The endpoint path is mildly redundant but does aid debugging and confirms scope, so it largely 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 no-output-schema list tool whose parameters are fully documented, the description covers scope and the underlying operation. The only real gap is distinguishing itself from fireworks_list_deployed_models.

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 100%, so all four parameters (including filter and pageToken) are documented in the schema itself. The description adds no filter syntax or pagination semantics beyond that, 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 and resource ('List deployments') and clarifies the domain term with '(serving instances) in the account', which helps an agent understand what a deployment is. However, it does not differentiate from the confusable sibling fireworks_list_deployed_models, so it falls short of the 5 bar.

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, no prerequisites, and no naming of alternatives. The sibling fireworks_list_deployed_models is close enough in meaning that an agent could easily pick the wrong one, and the description offers no disambiguation.

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?

readOnlyHint=true already tells the agent this is a safe read; the description adds that it is a control-plane call hitting a specific endpoint, which is useful for an agent reasoning about side effects. It says nothing about result ordering, caps on returned jobs, or pagination 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 short sentences, zero waste, with the scope statement front-loaded before the endpoint detail. Nothing is padded or repeated from structured 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 simple read-only list tool with full schema coverage and no output schema, the description covers purpose and scope adequately. It is slightly thin on pagination guidance, but the schema's pageToken description covers that.

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 pageSize, pageToken, and account_id are all already documented with semantics and constraints. The description adds no parameter-level detail beyond what the schema provides, so 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 ('List') and resource ('supervised fine-tuning jobs') scoped to the account, which clearly distinguishes it from list_datasets, list_deployments, and get_fine_tuning_job. It does not explicitly name a sibling it should not be used for, but the resource is 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?

No when-to-use guidance, no mention of the singular get_fine_tuning_job alternative, and no note about pagination workflow despite pageSize/pageToken existing. The agent must infer usage entirely from the name.

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

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

Annotations already declare readOnlyHint=true, covering the safety profile. The description adds useful context that this is a control-plane operation and the exact GET endpoint, but does not disclose pagination behavior, auth requirements, or rate limits beyond the account_id override documented in the schema.

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 no wasted words. The purpose is front-loaded, followed by concise technical context; every sentence 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 read-only list tool with fully described parameters and readOnlyHint annotations, the description supplies the scope (base + fine-tuned) and API endpoint. It does not explain pagination or return structure, but no output schema exists and pagination parameters are documented in the schema.

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

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

Schema description coverage is 100%, so all five parameters are fully documented in the input schema. The description adds no parameter meaning beyond what the schema already provides, making the baseline score of 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?

States a specific verb and resource: 'List models in the account (base + fine-tuned).' The parenthetical scope implicitly separates it from list_deployed_models and get_model, but it does not explicitly name alternatives, keeping it at 4 rather than 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?

Provides no guidance on when to use this tool versus siblings like fireworks_get_model or fireworks_list_deployed_models. The description only asserts the operation and endpoint, leaving selection conditions unstated.

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 already declare readOnlyHint=true, so the safe-read profile is covered. The description adds the backing endpoint (GET /v1/accounts/{account_id}/users) and confirms it is a control-plane read, but says nothing about pagination behavior, result ordering, or what identity/permissions are needed.

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 with zero filler, and the resource identity is front-loaded ahead of the implementation detail. 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 read-only, zero-required-parameter list tool with no output schema and safety already covered by annotations, this is nearly sufficient. It could note whether results are paginated and scoped strictly to the account, but nothing essential for calling it correctly is missing.

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

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

Schema description coverage is 100%, so the schema already documents pageSize, pageToken, and account_id in full. The description adds no parameter-level meaning beyond that; baseline 3 applies when structured data does the heavy lifting.

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

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

States a specific verb+resource ('List account members (users)') and even disambiguates the ambiguous term 'users' as account members. It is clearly distinct from the list_* dataset/model/deployment siblings, though it never names them explicitly to route the agent.

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 or when-not-to-use guidance and no named alternative. The only usage cue is the implicit 'Control-plane' label, which hints at an account-level admin API but leaves the agent to infer when this is the right call.

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