submit_personality_perceptionSubmit exactly 20 canonical Mini-IPIP predictions through one exact code capability. Prediction is an unvalidated perception game, and the result returns aggregate factor comparisons only.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | ||
| responses | Yes | ||
| participantKey | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
It discloses useful behavioral facts beyond the annotations: the game is 'unvalidated' and the response contains only 'aggregate factor comparisons'. However, with all annotations false, it remains silent on idempotency, repeat submissions, code validation failures, or any side effects beyond submission.
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 sentences convey the core constraint, the nature of the task, and the response limitation with minimal wordiness. It is front-loaded with the most important requirement ('exactly 20') before the caveats.
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 plus a detailed output schema cover the item set, count, and result granularity. Still, it omits what participantKey represents and how to obtain a valid code, which are necessary for an agent to invoke the tool correctly in the surrounding challenge workflow.
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 0%, and the description does not explain the three parameters by name. The phrase 'exactly 20 canonical Mini-IPIP predictions' clarifies the responses array's intent, but participantKey and the nature and provenance of code are left entirely to inference from the schema.
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?
Description states a specific action ('Submit'), a precise resource ('exactly 20 canonical Mini-IPIP predictions'), and a delivery mechanism ('one exact code capability'). This clearly identifies the tool's function and differentiates it from sibling submission/scoring tools such as submit_friendship_prediction.
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?
The description implies the tool is for submitting Mini-IPIP perception predictions of exactly 20 items, giving a sense of when it applies. However, it never names alternatives or states when not to use this tool, leaving the agent to infer the boundary against siblings like score_personality_responses.
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.
Each tool targets a distinct resource or flow, and the descriptions include strong qualifiers like 'exact opaque code' or 'issued challenge and nonce'. However, cast_ballot, submit_friendship_prediction, and submit_personality_perception all represent submission actions and could be misselected if the agent does not carefully match the exact challenge type.
Tool names follow a consistent verb_noun snake_case pattern throughout, dominated by get_ for retrieval and submit_ for submissions, with unique verbs like cast_, create_, request_, and score_ standing out clearly. There are no mixed casing styles or unpredictable naming conventions.
14 tools is well within the ideal range and each tool appears to serve a distinct purpose across five clear subdomains: daily ballots, friendship challenges, personality perception, scoring, and aggregate results. The count feels intentionally scoped rather than bloated or thin.
Core lifecycle paths are present for ballots, friendship predictions, personality perception, and result retrieval. Minor gaps exist around explicit creation of private challenges and any update or cancel operations, but those appear intentionally constrained by the server's privacy and immutability model.