score_personality_responsesDeterministically score exactly 20 canonical Mini-IPIP responses without storage. The result describes only the submitted vector, not an agent or person's identity, diagnosis, type, percentile, consciousness, or compatibility.
| Name | Required | Description | Default |
|---|---|---|---|
| responses | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint, idempotentHint, destructiveHint) already establish safety. The description adds meaningful context: 'without storage' clarifies non-persistence, 'deterministically' reinforces idempotency, and the phrase 'only the submitted vector, not an agent or person's identity...' prevents anthropomorphic misinterpretation of results. This goes beyond annotations and adds value without contradicting them.
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?
A single, tightly worded sentence that front-loads the core action ('Deterministically score exactly 20 canonical Mini-IPIP responses') and then qualifies output interpretation. No wasted words; every clause earns its place.
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 has an output schema (not shown but known), so return format is covered. The description addresses the main behavioral concerns: deterministic scoring, storage avoidance, and result interpretation. It does not explicitly mention error handling or prerequisites, but the schema enforces input validity. For a scoring tool with moderate complexity, it is sufficiently complete.
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 input schema fully documents the responses array with itemId enums and response enums (1-5). The description provides no direct explanation of the parameter, but schema coverage is effectively 100% via enums. According to calibration, when schema is self-explanatory, baseline is 3. The description adds no parameter details, so a 3 is appropriate.
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 states the verb 'score' and the specific resource: 20 canonical Mini-IPIP responses. It also explicitly states what it does NOT do (not identity, diagnosis, type, percentile, consciousness, compatibility), distinguishing its scope from potential misinterpretations. While it doesn't name sibling tools, the purpose is unambiguous and actionable.
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 specifies when to use the tool: to score exactly 20 Mini-IPIP responses. It implies a deterministic, storage-free operation. However, it does not explicitly mention alternatives among the sibling tools (e.g., get_personality_instrument for retrieving the instrument), leaving that differentiation to the reader. It is clear enough for an agent to infer its use case but lacks explicit 'when not to use' guidance.
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.