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Minds: Synthetic Market Research Panels

List Study Drafts

list_study_drafts
Read-onlyIdempotent

Lists durable unfinished study drafts, or returns the complete saved planning state for one exact draft ID. Draft records are distinct from running or completed studies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
draftIdNoExact study draft ID to retrieve. Omit to list all resumable study drafts owned by the authenticated user.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description builds on that by adding that it covers durable unfinished drafts and returns the complete saved planning state for an exact ID. No contradiction is present, and the additional context is useful for invocation.

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

Conciseness5/5

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

Two tight sentences deliver the core function and key distinction with no filler. The most important usage distinction is front-loaded before the clarifying sentence about draft records.

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?

For a tool with a single optional parameter and read-only annotations, the description covers what it lists, what it retrieves by ID, and how drafts relate to other study statuses. The absence of an output schema means return format details are not fully specified, but the description gives enough context for effective selection and use.

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

Parameters4/5

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

The schema already fully documents the optional draftId with 100% coverage, so the baseline is 3. The description adds meaningful operational meaning beyond the schema by linking draftId omission to listing and draftId presence to returning saved planning state.

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

Purpose5/5

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

The description names a precise verb and resource: listing durable unfinished study drafts or retrieving a complete saved planning state for one draft ID. It also explicitly distinguishes draft records from running or completed studies, which differentiates the tool from planning/run siblings.

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

Usage Guidelines4/5

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

The description gives clear context by describing both operating modes and noting that drafts are separate from running or completed studies. It implies when to use this tool for resumable drafts rather than active studies, though it does not explicitly name alternative sibling tools or provide direct when-not-to-use guidance.

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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TDQS

A3.9/5.0
Disambiguation3/5

The tool set has three distinct get_panel_* tools and two draft-saving tools (plan_panel_study, save_study_draft) that could be confused, but the detailed descriptions clarify their specific scopes. Most other tools (list, create, export, ask) target clearly different resources or actions.

Naming Consistency5/5

All tool names follow a consistent verb_noun scheme in snake_case (list_, get_, create_, ask_, export_, plan_, run_, save_). Verb choice maps predictably to the operation, making the set easy to navigate.

Tool Count4/5

At 18 tools, the set is slightly above the ideal 3-15 range but well-scoped for a comprehensive research-panel platform. Each tool addresses a distinct part of the workflow, from group/panel creation to study planning, execution, and export.

Completeness4/5

The surface covers the full research lifecycle: create groups/panels, ask questions, monitor status, export artifacts, and plan/run multi-question studies. It lacks update/delete operations for groups and panels, but these are minor gaps that agents can work around for typical research flows.