find_userLook up a speedrunner by username. Returns matching users with their ID, display name, and profile weblink. Example: find_user({ name: "cheese05" })
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Speedrunner username to look up, e.g. "cheese05" | |
| _apiKey | No | Optional speedrun.com API key for authenticated access; omit to use the shared platform key |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is consistent with the read-only annotation and adds that it returns user ID, display name, and profile weblink, plus an example. However, it does not disclose matching behavior (e.g., exact vs partial matches) or pagination. With annotations covering safety, this is adequate but not rich.
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?
Two concise sentences plus a concrete example. Every element is useful and front-loaded with the action.
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 tool is simple and the description covers purpose, example, and return fields. It does not mention edge cases like multiple matches, but with no output schema, the description adequately conveys the expected result.
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 coverage is 100% for both parameters. The description's example clarifies the 'name' parameter usage but adds minimal value beyond the schema's property descriptions.
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 uses a specific verb ('Look up') and resource ('a speedrunner by username'), and states the return fields (ID, display name, profile weblink). It clearly distinguishes from sibling tools like search_games or get_leaderboard.
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?
Usage is implied by the tool name and description, but there is no explicit guidance on when to use this tool versus alternatives like entity_profile or resolve_entity. No exclusions or alternative comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have distinct purposes, but there is overlap in data querying tools (ask_pipeworx, ask_pipeworx_grounded, deep_research, entity_profile, etc.) and prediction market tools (bet_research, polymarket_arbitrage, polymarket_edges, etc.). Detailed descriptions help differentiate them, but the number of similar-sounding tools increases the chance of misselection.
Tool names show mixed conventions: some use verb_noun (e.g., find_user, list_subscriptions), others are noun_verb (e.g., entity_profile, bet_research), and there are prefixes like polymarket_ and pipeworx_. While subgroups are internally consistent, the overall set lacks a unified pattern.
With 34 tools spanning speedrun.com queries, Pipeworx data access, memory management, subscriptions, and prediction markets, the server bundles multiple domains. The scope is too broad for a coherent single server; splitting into separate servers would improve usability.
Within each domain (speedrun.com, Pipeworx, Polymarket), the tool set covers key operations comprehensively, including research, arbitrage, fill risk, and monitoring. Minor gaps exist (e.g., no tool to place bets), but the overall surface is well-covered for the advertised functionalities.