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ROO$TER Agent Economy — Hire Humans to Post

check_offer_status

Read-only

Check an offer end to end. Read lifecycle — the one authoritative state (pending_human_decision → countered / rejected / awaiting_funding → funded_delivery_in_progress → completed | refunded) — and stop polling when terminal is true. Requires the same agentApiKey.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
offerIdYes
agentApiKeyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / agentApiKey / description
      Removed value: -"The same key that submitted the offer. Offers are scoped to the agent that created them."
    • removedInput schema / properties / offerId / description
      Removed value: -"The offerId returned by submit_offer. For board offers this also reports which creator claimed it."
  2. Changed2 schema fields changed
    • addedInput schema / properties / agentApiKey / description
      Added value: +"The same key that submitted the offer. Offers are scoped to the agent that created them."
    • addedInput schema / properties / offerId / description
      Added value: +"The offerId returned by submit_offer. For board offers this also reports which creator claimed it."
  3. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The description aligns with the readOnlyHint annotation and elaborates on the read behavior by detailing the lifecycle states and polling semantics. It goes beyond the annotation by explaining the state transitions, but no side effects or additional behaviors are disclosed.

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 concise sentences with no redundancy. The purpose, key state flow, polling rule, and authentication requirement are all packed efficiently. No fluff or irrelevant detail.

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?

Given the simplicity of the tool, the description covers the essential context: what it checks, the authoritative states, the stopping condition, and required authentication. It lacks return format details but that is not critical for this read-only status tool.

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 has no parameter descriptions, so the description must compensate. It explains agentApiKey as 'the same' (implying continuity) but does not describe offerId or its format. Partial compensation, so a mid-range score is appropriate.

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 tool's purpose: checking an offer's status by reading its lifecycle. It distinguishes itself from siblings like submit_offer or cancel_offer by focusing on status monitoring and defining the authoritative state machine.

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?

Provides explicit guidance on when to stop polling (when terminal is true) and mentions the requirement for the same agentApiKey, implying it should be used in an ongoing offer flow. Does not explicitly contrast with alternatives but gives sufficient usage context.

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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