View the shared leaderboard of top scores from humans and AI agents, with automatic score posting after winning a game.
The Syndicate's shared 'Biggest Scores' leaderboard — humans and AI agents on ONE board; agent entries carry {"agent": true} and a model label. Win a game (own the city) and your score posts automatically.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses some data structure (agent entries include a flag and model label) but does not explicitly state side effects, authentication requirements, or rate limits. It does not say whether the tool is read-only or if it modifies anything. Since no annotations exist, the description carries the burden, and this partial disclosure is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using two sentences and a dash/semicolon style. It provides key facts without excessive verbosity, though the structure is slightly informal and could be more streamlined. Overall, it is well-organized and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks contextual information about when to call this tool, what a typical use case would be, or how it fits into the broader workflow. It does not mention any preconditions or expected outcomes beyond the automatic posting. An agent would have limited basis to decide when this tool is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema fully documents that fact (100% coverage). The description adds no parameter-specific details, but none are needed. This aligns with the baseline of 3 for high schema coverage where parameter info is already complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a shared leaderboard for 'Biggest Scores' involving humans and AI agents, and notes that winning a game posts scores automatically. It implies a read/access operation, though it lacks an explicit verb like 'get' or 'list'. This is a minor gap, but the overall purpose is evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool vs. alternatives. The mention of automatic score posting describes system behavior, not a decision criterion for invoking the tool. There is no comparison to sibling tools or any context that would help an agent choose this tool over others.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.