prepare_check_requestReturn the paid REST request shape for screening one or two supplied materials. The agent price is $0.99.
| Name | Required | Description | Default |
|---|---|---|---|
| material_count | Yes | ||
| total_characters | Yes | Combined readable-text character count after extracting the supplied materials. |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds meaningful context beyond those annotations: the operation is paid ($0.99) and returns only a request shape rather than executing the screening. This is useful behavioral 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?
Two short sentences with no filler. The core behavior is front-loaded, and the price detail is relevant and succinctly placed.
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, read-only, idempotent tool with an output schema, the description is nearly complete: it gives purpose, material-count limit, and cost. It could more explicitly distinguish itself from prepare_instant_brief_request, but the title and sibling context reduce that 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?
The schema describes total_characters well, and the description's 'one or two supplied materials' partially conveys material_count's meaning. With only 50% schema coverage, the description compensates somewhat but leaves the exact relationship between the supplied materials and the two numeric parameters implicit.
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?
Clearly identifies the verb (Return), the resource (paid REST request shape for screening), and the scope (one or two supplied materials). It distinguishes itself from the get_* sibling tools, which fetch PDFs/results rather than preparing a request.
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 use when preparing a check-screening request for one or two materials, and the title separates it from prepare_instant_brief_request. However, it does not explicitly state when not to use this tool or name a preferred alternative.
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.
The paired get_check_* and get_instant_brief_* tools are clearly separated by product prefix, and prepare_* tools have distinct purposes. The only slight overlap is list_reglayer_products, which appears to be the broader catalog containing the Instant Brief products listed by list_instant_brief_products.
Every tool follows a predictable verb_noun pattern with get_, list_, and prepare_ prefixes and product-specific suffixes. The Check and Instant Brief groups are symmetrically named, making the API surface easy to navigate.
Ten tools is well-scoped for a dual-product regulatory research server. Each tool covers a distinct step in the workflow: product discovery, request preparation, status polling, result retrieval, and PDF download.
The tool surface forms a complete workflow: list products, prepare a purchase request, poll status, then retrieve structured results and authenticated PDFs. No obvious dead ends or missing operations within the stated domain.