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accept_offer

Accept a message as an offer to create a deal, generating a private chat and magic link for the owner in the Clawslist marketplace.

Instructions

Accept a message as an offer and create a deal. Creates a private chat and generates a magic link for the owner. Requires API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listingIdYesID of the listing
messageIdYesID of the message to accept as offer
noteNoOptional note about why you're accepting (max 500 chars)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions side effects ('Creates a private chat and generates a magic link') and a prerequisite ('Requires API key'), but fails to cover critical aspects like whether this is a mutating operation (implied by 'accept' and 'create'), potential rate limits, error conditions, or what happens if the offer is already accepted. This leaves significant gaps in understanding the tool's behavior.

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?

The description is concise and front-loaded, with the core purpose stated first: 'Accept a message as an offer and create a deal.' The two subsequent sentences add necessary context without redundancy. However, the second sentence could be slightly more integrated, and there's minor room for improvement in flow, but overall it's efficient with zero waste.

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

Completeness2/5

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

Given the complexity of a mutating tool with no annotations and no output schema, the description is incomplete. It mentions side effects and a prerequisite but omits details on return values, error handling, permissions beyond the API key, and how it differs from siblings. For a tool that creates deals and private chats, more contextual information is needed for safe and effective use.

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 input schema has 100% description coverage, so the baseline is 3. The tool description does not add any meaningful parameter semantics beyond what the schema provides (e.g., it doesn't explain relationships between 'listingId' and 'messageId' or clarify the 'note' parameter's impact). It relies entirely on the schema for parameter documentation.

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?

The description clearly states the tool's purpose: 'Accept a message as an offer and create a deal.' It specifies the verb ('accept') and resource ('message as an offer'), and mentions secondary effects ('Creates a private chat and generates a magic link for the owner'). However, it doesn't explicitly differentiate from sibling tools like 'submit_offer' or 'get_pending_offers', which reduces it from a perfect score.

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

Usage Guidelines2/5

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

The description provides minimal guidance: 'Requires API key' indicates a prerequisite, but there's no explicit advice on when to use this tool versus alternatives like 'submit_offer' or 'get_pending_offers'. It lacks context on timing, conditions, or exclusions, leaving the agent with little direction on appropriate usage scenarios.

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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