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Start a study: request a quoted campaign

campaign_request

No key needed. Sends a study request to a person and returns a request_id, the tier that fits, the price band, what we still need from you, the next step and the claim scope. Nothing is run or charged. Call it after reading a guide.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gridNoFree text: compositions x temperatures, or ligands x pockets (e.g. 3 ligands x 1 receptor)
questionYesOne paragraph: the decision the study feeds
data_rulesNoHow the data and results may be used, kept or shared
organizationNoOptional
contact_emailYesWhere the reply goes
customer_typeYesmineral-processing | dark-proteins | semiconductor | other
inputs_availableNoWhat you can supply now, e.g. bath range, AlphaFold model, ligand list

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations mark this non-read-only and non-idempotent, so the key question is what actually happens — and the description answers it: 'Nothing is run or charged' and 'No key needed'. It also enumerates the response payload (request_id, tier, price band, gaps, next step, claim scope), which is meaningful behavioral context beyond the annotation flags.

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

Conciseness4/5

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

Three short sentences, front-loaded with the key fact (no key needed) and the consequence (nothing is run or charged). The middle sentence is a dense list but every item earns its place given there is no output schema.

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

Completeness4/5

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

No output schema exists, so the description usefully enumerates returned fields, and it states the non-committal nature of the call. It is close to complete for an agent deciding whether to invoke it; only the precise relationship to the job-execution siblings is unstated.

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

Parameters3/5

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

Schema description coverage is 100%, so all seven parameters are already documented in the schema; the description adds no parameter-level semantics such as format for grid or data_rules. Baseline 3 is appropriate when the schema carries the whole burden.

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

Purpose4/5

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

States a specific action and outcome: 'Sends a study request to a person and returns a request_id, the tier that fits, the price band...'. This is clearly a quoting/request step rather than a job execution, which distinguishes it from create_job/start_job/submit_job without naming them explicitly.

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

Usage Guidelines3/5

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

'Call it after reading a guide' gives one sequencing hint and implicitly routes to the guide sibling. However it never states when to use this versus start_job or create_job, nor any preconditions tied to contact_email or customer_type. Usage is implied rather than explicit.

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

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