List generated reports in your clariBI organization. Returns id, title, status, output format, and download URL.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Page size (1-100). | |
| offset | No | Row offset for pagination. | |
| status | No | Filter by status (pending, generating, completed, failed, cancelled). |
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | ||
| limit | Yes | ||
| total | Yes | Total reports matching the query. | |
| offset | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds the organization scope and lists return fields (id, title, status, output format, download URL), but does not disclose pagination behavior, default ordering, or that all statuses are included. This adds some context but not deep behavioral detail.
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 action and resource, followed by a concise list of return fields. 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?
The tool is a simple list operation with output schema present, and schema covers parameters. The description adequately scopes the operation and return data. Minor ambiguity around the word 'generated' could be confused with a status filter, but the schema disambiguates via the status enum. Overall sufficient for an agent.
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?
Input schema descriptions cover 100% of parameters with clear meanings and defaults. The description does not reference parameters, but the schema already provides sufficient semantics, 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?
The description uses the specific verb 'list' with resource 'generated reports' and scopes it to 'your clariBI organization'. It distinguishes from siblings like get_report (single report) and other list_* tools by explicitly naming the report resource and return fields.
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 for browsing reports but does not explicitly contrast with get_report or mention when to prefer this tool over alternatives. No exclusions or preconditions are stated, so it is clear but not explicitly guided.
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.
Tools are generally distinct by resource and action, but a few status polling tools (check_integration_status, get_analysis_status) could be confused without careful reading; descriptions clarify the difference.
Most tools use a consistent verb_noun snake_case pattern, but there is minor variation (e.g., 'check' vs 'get' for status, and some compound nouns like 'request_oauth_integration_url').
26 tools is slightly above the typical range but appropriate for a comprehensive BI platform covering data ingestion, analysis, forecasting, reports, dashboards, and account management; each tool has a clear purpose.
The tool surface is heavily read-oriented, lacking update and delete operations for most resources (data sources, dashboards, reports, forecasts). This leaves significant lifecycle management gaps for an agent.