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RigorLoop Research Bounties

Create Research Bounty Draft

create_bounty_draft
Idempotent

Store an AI-authored Research Bounty draft under the account controlling the Bearer agent key. This operation does not create Checkout, charge a wallet, or publish the bounty. Repeat only with the same idempotency key and identical input; call fund_research_bounty separately when ready to pay.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldYes
titleYes
currencyNoUSD
questionsNoOptional private review questions, visible only after an expert is selected. Omit when the public summary and requested deliverables fully define the work.
claim_typeNopaper_review
source_urlsNoOptional private HTTPS source links, visible only to the selected expert. Omit for a self-contained Research Bounty.
public_summaryYes
idempotency_keyYesUnique URL-safe key. Reuse it only to retry this identical draft.
review_window_daysYes
bounty_amount_centsYes
requested_deliverablesYes
requested_qualificationsNoOptional expert qualifications. Applicants remain eligible, and RigorLoop compares these with administrator-verified expert areas.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataNo
toolYes
errorNo
statusYes
requestIdYesStable RigorLoop request identifier for support and integration feedback.
nextActionNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already signal idempotency (idempotentHint=true) and non-read-only behavior (readOnlyHint=false). The description adds valuable context by confirming the draft is stored under the account controlling the Bearer agent key and by clarifying that no payment or publication occurs. This goes beyond the annotations, though it does not disclose every potential side effect (e.g., validation, storage limits).

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 three sentences, front-loaded with the primary purpose, and every sentence contributes meaningful information (what it does, what it doesn't do, and retry/next-step guidance). No wasted words.

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 description situates the tool within a workflow (draft before payment) and clarifies side-effect boundaries. With an output schema present, return value details are not required. It could mention prerequisites (e.g., authenticated agent) or validation behavior, but overall it provides sufficient context for a draft-creation tool.

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

Parameters2/5

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

The schema description coverage is only 33%, so the description needs to compensate by explaining key parameters. However, it only mentions the idempotency key and 'identical input'; it provides no added meaning for major required parameters like title, bounty_amount_cents, review_window_days, or requested_deliverables. The description adds minimal value for parameter understanding.

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 uses a specific verb ('Store') and clearly identifies the resource ('an AI-authored Research Bounty draft'). It distinguishes the tool from siblings by explicitly stating what it does NOT do (create Checkout, charge a wallet, publish) and by referencing the separate funding step.

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

Usage Guidelines5/5

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

The description provides explicit usage guidance: it states the draft creation is a separate step from payment ('call fund_research_bounty separately when ready to pay') and gives clear retry instructions ('Repeat only with the same idempotency key and identical input'). This effectively tells when to use this tool and when to use an alternative.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct entity or action: draft creation, funding, quote, file upload, applications, expert selection, result viewing/acceptance, status, and search. There is no overlap or confusion between tools.

Naming Consistency5/5

All tool names follow a consistent verb_noun snake_case pattern, using clear verbs like create, fund, get, list, prepare, complete, accept, select, search, and report. The pattern is uniform across the entire set.

Tool Count5/5

Twelve tools is appropriate for a research bounty platform, covering the full workflow without redundancy. Each tool has a clear role, and the count is within the ideal range.

Completeness5/5

The tool set covers the complete bounty lifecycle: draft creation, funding, file upload, applications, expert selection, status tracking, result review, and acceptance/contest. It also includes a quote and a search function for public bounties, plus a feedback channel, leaving no obvious gaps.

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