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ty-meador

civ-v-llm-harness

by ty-meador

accept_deal

Accept an incoming trade proposal from another leader in Civilization V to finalize the deal and see its effects. Use when a deal is already on the table.

Instructions

Accept an incoming trade already on the table (see incoming_deal). Does not construct a new deal. To make an offer of my own use propose_deal. The answer carries the AI's remark, the accepted_items and measured effects (gold per turn, deal count, resources before vs after); new_deal is the row the deal now holds in current_deals (a renewal's offered rows carry the old deal's end; the new end replaces it, the offered one stays as final_turn_offered). When another leader is queued behind this one (several can wait at a turn start), the answer carries still_pending: true, next (their screen, words, buttons and the deal on the table) and the gate it raises: answer that one next, no discussion() read needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.11.0

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations at all, the description carries the full burden and does so well: it enumerates the return payload (remark, accepted_items, effects, new_deal), explains the renewal row semantics (offered end vs final_turn_offered), and discloses the multi-leader queue behavior (still_pending, next, gate). This is behavioral context an agent could not derive from the empty schema.

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 core action and the sibling routing are front-loaded in the first two sentences. The remainder is dense but information-bearing, covering returns and the queue/gate flow. A few clauses are syntactically heavy (the parenthetical on current_deals), which costs it the top mark.

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?

There is no output schema and no annotations, so the description must supply both the safety/behavior profile and the return shape — and it largely does. Remaining gaps are failure modes (e.g. what happens if the deal was already withdrawn) and any preconditions, but coverage of the success path and the pending-leader gate is strong.

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

Parameters4/5

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

The tool takes zero parameters, so the baseline is 4 per the rubric. There is nothing for the description to clarify or compensate for on the input side.

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?

Opens with a specific verb+resource ('Accept an incoming trade already on the table') and immediately anchors to the sibling that surfaces it (incoming_deal). It also explicitly excludes the sibling it is not ('Does not construct a new deal'). The distinction from propose_deal is stated outright.

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?

Explicitly states when to use this tool (an offer already on the table), when to use the alternative (propose_deal 'To make an offer of my own'), and gives a routing rule for the pending-leader case (answer the next screen, no discussion() read needed). Nothing is left to inference.

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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