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LiveScore MCP by Nova (CIVAI)

resolve_vs_query

First step for any Team A vs Team B query. Resolves the best matching fixture (live, today FT, most recent past, or upcoming) using Google suggest normalization and inferred-league scan. Returns match_id plus structured home/away teams, or found: false. Do not guess match ids.

Input Schema

NameRequiredDescriptionDefault
queryYesFull user vs phrase (e.g. Inter Miami vs Montreal, Arsenal vs Chelsea score).
notification_messageNoShort user-facing sentence for this action if the follow-up reply fails. Plain text only; do not mention template syntax or variable names.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the resolution priority (live, today FT, most recent past, upcoming), the normalization strategy, and the return contract including the found: false failure case. It omits tie-breaking behavior when several fixtures match and any latency/rate characteristics.

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?

Three sentences, front-loaded with the routing rule, then resolution logic, then return shape and the anti-pattern warning. The implementation detail about suggest normalization earns its place by justifying fuzzy input handling.

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?

No output schema exists, and the description compensates by describing the return value (match_id plus structured home/away teams, or found: false). It could go further by saying the returned match_id is meant to be passed to get_match/get_live_scores, but an agent has enough to call it correctly.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning: it tells the agent the query is a full 'Team A vs Team B' phrase that gets Google-suggest normalized and league-inferred, so the input need not be exact. notification_message is left entirely to the schema, which is acceptable given full coverage.

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?

States a specific verb (resolves) and resource (the best matching fixture for a Team A vs Team B query), and positions itself as the entry point of a workflow rather than a fetcher like get_match or get_live_scores. The 'Do not guess match ids' line makes the boundary against guessing/get_match-by-id explicit.

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?

Gives a clear trigger ('First step for any Team A vs Team B query') and an explicit prohibition ('Do not guess match ids'), which tells the agent when to route here rather than fabricate an id. It does not name a specific sibling as the fallback/alternative, so it stops short of full when/when-not/alternatives coverage.

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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