score_interaction_signalsCalculate transparent interaction shares and rates from user-supplied aggregate chat counts without scoring affection, intent, compatibility, or personality.
Calculate transparent shares and rates from user-supplied aggregate counts without scoring affection, intent, compatibility, or personality.
| Name | Required | Description | Default |
|---|---|---|---|
| participants | Yes |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds a valuable behavioral scope statement: it is a deterministic calculator of shares/rates that explicitly performs no affection/intent/compatibility/personality judgment. It omits return format, but that is a modest gap against the covered safety profile.
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 sentence that leads with the action and follows with the scope exclusion. There is no filler and every clause carries information.
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?
Given a complex input (2-20 participant objects, seven required counts each) and no output schema, the description explains the conceptual purpose but not the per-field input expectations or the returned shares/rates. The exclusion clause is helpful, but the definition is not fully self-sufficient for correct invocation.
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% for the single participants parameter, a complex array of objects with seven required numeric counts each. The description hints at the input shape via 'user-supplied aggregate counts' but never enumerates or explains the required per-participant fields, so it only partially compensates for the schema's silence.
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 names a specific action (calculate) and resource (shares and rates from aggregate counts), and it fences off a whole class of functions by stating it does not score affection, intent, compatibility, or personality. This makes its purpose concrete and separates it from interpretive/scoring tools. It stops short of naming which sibling to use instead, so it is clear but not sibling-differentiated.
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 phrase 'from user-supplied aggregate counts' implies the caller must pre-aggregate, and the negative clause signals this is not the tool for qualitative scoring. However, no explicit when-to-use condition or named alternative (e.g., build_chat_analysis_brief) is given, so the guidance is only implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.