Encode SNN state into a latent space to enable compact representation and downstream analysis.
Encode SNN State to Latent Space
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "wm_encode"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v3.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint=false and idempotentHint=false, so this is a state-touching, non-repeatable operation, yet the description adds nothing about what state is affected, whether it must follow snn_step, or what a repeated call does. It does not contradict the annotations, but it also contributes no behavioral context beyond 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 front-loaded sentence with no filler, which is appropriate for a short definition. It is efficient, though it is arguably terse to the point of under-specification.
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?
This is a non-trivial world-model operation with no output schema, no parameter documentation, and no explanation of the returned latent representation or the required input state. For an agent to invoke it correctly in a pipeline of wm_* tools, considerably more context is needed.
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 takes zero parameters, so per the rubric the baseline is 4 and the empty schema needs no further explanation. Nothing in the description is needed to compensate.
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?
States a specific verb (Encode) and resource pair (SNN State -> Latent Space), so the transformation is understandable. It does not differentiate itself from siblings like wm_predict, wm_plan, or wm_surprise, which also operate on the world model, so the agent must infer the boundary.
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?
No indication of when to call this versus wm_predict or wm_surprise, no prerequisites (e.g. requiring a current SNN state), and no mention of ordering within a world-model cycle. The agent gets no routing guidance at all.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.