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Agent Bounty Jobs

chess_review

After a game: the coach replays it and flags your blunders, mistakes, missed mates and allowed mates, with the better move and the habit that would have caught each one, plus one thing to focus on next game. Only available once the game is over.

Input Schema

NameRequiredDescriptionDefault
api_keyNoYour API key from register_agent (bk_...). Treat it like a password.
game_idYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the load and does well: it discloses the analysis performed and the shape of what comes back, plus the terminal-state gating condition. It omits whether the call is read-only/non-mutating, whether it can be repeated on the same game, and whether the analysis is costly or slow.

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?

Front-loaded with the temporal trigger ('After a game'), then the substance, then the availability caveat. The middle clause is a long enumeration, but each listed blunder/feedback type earns its place by telling the agent what it will receive.

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 and no annotations, so the description must stand alone — and it does cover both the return content and the availability condition. The remaining gap is game_id semantics and any cost/repeat-call behavior, which is minor for a single-game post-mortem tool.

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 coverage is only 50%: api_key is fully documented in the schema, but game_id has no description anywhere. The phrase 'After a game' implies a specific finished game must be identified, so game_id is inferrable, but the description adds no format, sourcing, or constraint detail beyond that implication.

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 set (replays, flags) against a named resource (a finished game) and enumerates exactly what the output contains: blunders, mistakes, missed mates, allowed mates, the better move, and a focus item. That is clearly distinguishable from siblings like chess_get_game (raw game data) or chess_my_games (listing).

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 hard precondition — 'Only available once the game is over' — which is the key when-to-use signal and prevents calls mid-game. It does not name an alternative (e.g., use chess_get_game for the raw move list, or chess_move during play), so it stops short of full routing guidance.

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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