fireworks_get_datasetGet a single dataset by id. Control-plane: GET /v1/accounts/{account_id}/datasets/{dataset_id}.
| Name | Required | Description | Default |
|---|---|---|---|
| account_id | No | Fireworks account id. Overrides FIREWORKS_ACCOUNT_ID for this call. | |
| dataset_id | Yes | Dataset id (the resource segment). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations include readOnlyHint=true, so the description does not need to state safety. It adds the HTTP endpoint and path, which is consistent and reveals a bit about the API interaction, but no deeper behavioral traits (e.g., no pagination, no side effects).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no unnecessary words. It is front-loaded with the core purpose, then adds the HTTP reference. 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?
Given the complexity is low (simple retrieval, no nested objects, no output schema), and annotations plus schema cover safety and parameters, the description is adequate. It lacks details on return format or error handling, but that's acceptable without output 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 coverage is 100% and both parameters have descriptions explaining their purpose (account_id override and dataset_id resource segment). The description adds no extra meaning beyond the schema, 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?
The description explicitly states 'Get a single dataset by id.' This clearly indicates the action (get) and the resource (single dataset) with specific identification via id. It distinguishes from sibling tools like fireworks_list_datasets.
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 does not provide explicit guidance on when to use this tool versus alternatives like fireworks_list_datasets. The use case is implied (retrieving one dataset by id) but not clearly contrasted with listing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct resource and action combination (e.g., create_dataset vs delete_deployment vs list_models), with no overlapping purposes. Descriptions clearly differentiate each tool.
All tools follow a consistent 'fireworks_verb_noun' pattern, with verbs like create, delete, get, list and singular or plural nouns as appropriate. No mixing of conventions.
14 tools cover the main resources of the Fireworks platform (accounts, datasets, deployments, fine-tuning jobs, models, batch inference, users). The scope is appropriate and not overwhelming.
The tool set is heavily read-oriented with only one creation tool (create_dataset) and one deletion tool (delete_deployment). Missing create for deployments, fine-tuning jobs, models; missing update and delete for most resources. Gaps would hinder full workflow automation.