[wavefunction — demand-side agent/collective discovery] Distill a user's dialogue into an intention wavefunction (explicit intentions + confidence). dialogue: [{role, content}, ...].
[wavefunction — demand-side agent/collective discovery] Distill a user's dialogue into an intention wavefunction (explicit intentions + confidence). dialogue: [{role, content}, ...].
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | ||
| dialogue | Yes |
Changes observed during successful MCP inspections.
v0.1.13v0.1.12v0.1.11Input schema / properties / dialogue / itemsAdded value: +{
+ "additionalProperties": {
+ "type": "string"
+ },
+ "type": "object"
+}Input schema / properties / dialogue / titleAdded value: +"Dialogue"Input schema / properties / user_id / titleAdded value: +"User Id"Input schema / titleAdded value: +"intakeArguments"v0.1.9Input schema / properties / dialogue / itemsRemoved value: -{
- "additionalProperties": {
- "type": "string"
- },
- "type": "object"
-}Input schema / properties / dialogue / titleRemoved value: -"Dialogue"Input schema / properties / user_id / titleRemoved value: -"User Id"Input schema / titleRemoved value: -"intakeArguments"Input schema / properties / dialogue / itemsAdded value: +{
+ "additionalProperties": {
+ "type": "string"
+ },
+ "type": "object"
+}Input schema / properties / dialogue / titleAdded value: +"Dialogue"Input schema / properties / user_id / titleAdded value: +"User Id"Input schema / titleAdded value: +"intakeArguments"Input schema / properties / dialogue / itemsRemoved value: -{
- "additionalProperties": {
- "type": "string"
- },
- "type": "object"
-}Input schema / properties / dialogue / titleRemoved value: -"Dialogue"Input schema / properties / user_id / titleRemoved value: -"User Id"Input schema / titleRemoved value: -"intakeArguments"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It describes the core behavior of taking dialogue and outputting an intention wavefunction, but does not disclose side effects, mutability, or state changes. The tool name 'intake' suggests storage but description does not confirm.
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 sentences, front-loaded with context in brackets, and every word adds value. No redundancy or unnecessary detail.
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 no output schema, the description hints at the return value ('explicit intentions + confidence'), which is helpful. However, it lacks error handling, prerequisites, or details on confidence interpretation. Overall, it is fairly complete for a tool of this complexity.
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% (no parameter descriptions). The description adds meaning for the 'dialogue' parameter by specifying its format as '[{role, content}, ...]', but does not address 'user_id'. While it compensates partially, it would benefit from explaining both parameters.
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 tool 'Distill a user's dialogue into an intention wavefunction', using the specific verb 'distill' and resource 'intention wavefunction'. It also explains the output includes 'explicit intentions + confidence', which differentiates it from siblings like wavefunction__collapse that would likely handle subsequent processing.
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 provides domain context 'demand-side agent/collective discovery' but does not explicitly state when to use this tool versus alternatives like wavefunction__collapse or when not to use it. The usage is implied but lacks clear exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.