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The Tennis Desk

Desk level, match by match

query_match_log
Read-onlyIdempotent

Returns a player's match-by-match rating history for one season: each match they played, their level before and after it, and the other players on court with their levels then. Call it when someone asks how a player's level changed, how they reached it, what one result did to it, or asks to see their matches. Prefer it to query_player_history when the question is about the level rather than the results, because it follows the level match by match.

Input Schema

NameRequiredDescriptionDefault
askedNoThe person's question word for word, never paraphrased. Leave it out rather than invent one.
playerYesPlayer name as the member wrote it. Or the player's Desk page link or number.
seasonNoSeason year. Omit for the current season.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, closed-world behavior, so the description doesn't need to re-state safety. It does add value by disclosing the returned content in detail (per-match level deltas and opponents' contemporaneous levels), which matters since there is no output schema. It stops short of noting scope limits, such as whether a missing season or a player with no matches yields an empty result or an error.

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 purpose and return contents are front-loaded in the opening sentence, and the routing rule follows. It is two dense sentences with little wasted text, though the clause list of trigger phrasings is slightly verbose.

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?

With no output schema, the description does the right work by describing what comes back, and it names the sibling it competes with. The only gap is edge-case behavior — empty seasons, ambiguous player names, or whether the 'asked' parameter affects results — which an agent might want before calling.

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?

Schema description coverage is 100%, so all three parameters (asked, player, season) are already documented with usage notes in the schema. The description only echoes 'for one season' without adding format, fallback, or edge-case guidance beyond that. Baseline 3 applies when the schema carries the parameter burden.

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 first sentence names a specific verb and resource — returns a player's match-by-match rating history for one season — and enumerates the contents (level before/after each match, other players on court with their levels). That is enough to tell it apart from query_player_history, which it names explicitly.

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?

It gives concrete trigger phrasings (how a player's level changed, how they reached it, what one result did to it, show their matches) and an explicit routing rule: prefer this over query_player_history when the question is about the level rather than the results. Both when-to-use and which-alternative are stated.

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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