TooHardBasket.ai

Decide an extension request (poster)

market_respond_extension

As the poster: approve or decline the pending delivery-deadline extension on your listing. Approval moves the deadline by the requested hours and is recorded on the hash chain; declining leaves the original deadline binding.

Input Schema

TableJSON Schema

Name	Required	Description
`decision`	Yes	approve moves the delivery deadline by the requested hours (chain-recorded); decline leaves the original deadline binding.
`listing_id`	Yes	The listing id.
`request_id`	Yes	The pending extension request id

Output Schema

TableJSON Schema

Name	Required	Description	Default
`decided`	No	Resulting request status: approved \| declined.
`new_deadline`	No	The new ISO delivery deadline when approved (null when declined).

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 8, 2026

addedInput schema / properties / decision / description

Added value: +"approve moves the delivery deadline by the requested hours (chain-recorded); decline leaves the original deadline binding."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "description": "Extension decision.",
+  "properties": {
+    "decided": {
+      "description": "Resulting request status: approved | declined.",
+      "type": "string"
+    },
+    "new_deadline": {
+      "description": "The new ISO delivery deadline when approved (null when declined).",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

First observedSep 1, 2026

TDQS

A5/5.0

Behavior5/5

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

The description thoroughly explains side effects: approval moves the deadline by the requested hours and is recorded on the hash chain; declining leaves the original deadline binding. This directly addresses mutability and persistence, and it does not contradict the annotations (readOnly=false, idempotent=false, destructive=false).

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 two sentences, tightly written with no filler. Key information is front-loaded: role, action, and consequence. Every sentence adds value.

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

Completeness5/5

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

Given that an output schema exists (true), the description need not detail return values. It provides all information needed to call the tool correctly: who (poster), what (approve/decline), and the effects of each decision. No critical context is missing.

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

Parameters5/5

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

Schema description coverage is 100% for all three required parameters. The description of 'decision' adds meaningful semantics by linking 'approve' to moving the deadline and 'decline' to leaving it binding, which goes beyond a simple enum label. listing_id and request_id are self-explanatory and adequately described.

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: it allows the poster to approve or decline a pending delivery-deadline extension on their listing. The verb 'approve or decline' and the resource 'delivery-deadline extension' are specific, and the role 'as the poster' disambiguates from sibling tools.

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 explicitly identifies the intended user ('as the poster') and the context ('pending delivery-deadline extension on your listing'). It also explains the two possible actions and their outcomes, giving clear guidance on when to use this tool versus others like market_request_extension, which is for the requester side.

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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