get_personality_instrumentReturn the exact versioned public-domain Mini-IPIP 20 instrument. No response vector is submitted or stored.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations: the tool returns an exact versioned public-domain instrument and that no response vector is submitted or stored. No contradiction exists between the description and annotations.
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 two short sentences with no filler. The core purpose is front-loaded in the first sentence, and the second sentence adds essential behavioral clarification about side-effect-free retrieval.
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?
For a zero-parameter read-only retrieval tool with an output schema, the description fully covers what an agent needs to invoke it correctly. It explains what is returned (exact versioned Mini-IPIP 20 instrument) and that nothing is submitted or stored. No additional context is necessary.
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, so there are no parameter semantics to document. The description still adds value by clarifying the operation has no request payload (no response vector submitted). The 0-parameter baseline of 4 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 uses a specific verb ('Return') with an exact resource ('exact versioned public-domain Mini-IPIP 20 instrument'), making the tool's function unmistakable. It also distinguishes itself from submission or scoring tools by explicitly noting that no response vector is submitted or stored. This is strong differentiation against the sibling tools.
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 clearly implies when to use this tool: when retrieving the instrument rather than submitting responses. It provides useful contextual guidance through the sentence 'No response vector is submitted or stored,' but it does not explicitly name alternatives or exclusion conditions. This fits 'clear context, no exclusions'.
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.