Polymarket Leaderboard Scraper

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

Beyond the annotations (readOnly, openWorld, non-idempotent, non-destructive), the description discloses that it starts one Apify Actor run via mcp.apify.com, requires the caller's own APIFY_TOKEN, consumes the caller's Apify account quota, and only reads public web data. This auth, billing, and run-lifecycle context is exactly the kind of behavior the annotations cannot express.

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 labeled structure (purpose, When to use, Returns, Behavior, Docs) front-loads the key information and each block carries distinct content. The opening sentence slightly duplicates the title, and the field enumeration is long, but nothing is genuinely redundant.

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?

With no output schema, the description compensates by explaining the return shape (dataset rows as JSON, plus run and dataset IDs for paging) and the run-based execution model. It stops short of mentioning cost implications of large maxResults or failure behavior, 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.

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

Schema description coverage is 100%, with enums, defaults, and per-value explanations already present for category, timeRange, leaderboardType, and both boolean toggles. The description only restates the filtering axes ('time range, category, and ranking type') and adds no format or interaction details beyond the schema, so baseline 3 applies.

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 states a specific verb and resource ('Scrape Polymarket leaderboard rankings with full trader profiles') and enumerates the extracted fields (wallet addresses, P/L, volume, positions, trades, bios, social links). It is clearly distinct from the listed siblings, though it never names an alternative (e.g. the Kalshi scraper) to sharpen that boundary.

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?

An explicit 'When to use' line gives the triggering condition: needing Polymarket leaderboard rankings and trader profiles with P/L, volume, and positions. There are no exclusion rules or named alternatives, so an agent knows when to call it but not when to prefer something else.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.