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request_think_tank_revision

Spend a free revision turn on a completed think tank order. Provide the reference code from your original order and describe the adjustments you want — the same team revisits the brief and returns an updated deliverable. Poll get_result with the reference code to retrieve it. Free: no payment required, the turn is included with your order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
adjustmentsYesWhat you want the team to adjust, expand, or rethink.
referenceCodeYesThe TASTE-... reference code returned when you placed the think tank order.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tipYes
statusYes
messageYes
sessionIdYes
referenceCodeYes
turnsRemainingYes

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It reveals that the operation is free, that the same team revisits the brief, and that the deliverable is retrieved via polling 'get_result' rather than returning synchronously. This adds meaningful context about the async flow and cost.

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?

The description is four sentences, each earning its place: the action, the inputs, the workflow, and the cost. It is front-loaded with the primary verb and resource, and there is no redundant or extraneous wording.

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?

The tool is simple with two parameters and an output schema present. The description covers purpose, when to use, the retrieval mechanism, and the free nature. It is sufficiently complete for an agent to understand and invoke the tool, though it could explicitly mention any revision limits.

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?

The schema descriptions already cover both parameters fully: referenceCode includes the TASTE-... format and origin, and adjustments explains what to provide. The description repeats these requirements without adding new semantic details, so it does not exceed the baseline expected given 100% schema coverage.

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 clearly states the specific action: spend a free revision turn on a completed think tank order. It distinguishes from sibling tools like 'request_illustration_revision' (for illustrations) and 'order_think_tank_session_30/60' (for new orders) by explicitly targeting think tank revisions and noting the same team revisits the brief.

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 specifies when to use the tool: on a completed order, with the revision turn included. It also directs the user to poll 'get_result' for retrieval, indicating the workflow. While it does not explicitly list alternatives or exclusions, the context makes it clear this is for revisions rather than new orders.

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

A4.2/5.0
Disambiguation5/5

Each tool targets a specific action or domain, with clear distinctions between similar ones (e.g., review_content vs prepublish_review for different review purposes, order_think_tank_session_30 vs _60 by duration). No ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with underscores, e.g., list_offerings, verify_certificate, request_human_approval. No mixing of conventions.

Tool Count4/5

17 tools is on the higher side but fully justified given the broad scope: expert consultations, think tanks, content reviews, verification, and human approval. Each tool serves a distinct purpose.

Completeness4/5

Covers the full workflow from discovery to ordering, revision, and on-chain verification. Minor gaps exist (e.g., no order cancellation or history listing), but core operations are well-represented.