MorseByte x402 Edge Data Refinery & Quant Gateway

Multi-LLM Fast Inference Router

morsebyte_llm_router

Read-only

Route prompts to fast edge models (Llama 3.1 8B or Llama 3.3 70B) ($0.002 USDC via x402).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "morsebyte_llm_router"
  }
}

Input Schema

Name	Required	Description	Default
`tier`	No
`prompt`	Yes
`system`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedOct 21, 2026
- removedInput schema / properties / prompt / description
```
Removed value: -"User prompt to execute"
```
- addedInput schema / properties / system
```
Added value: +{
+  "type": "string"
+}
```
- removedInput schema / properties / tier / description
```
Removed value: -"Model tier: fast (8B) or smart (70B)"
```
AddedOct 19, 2026

TDQS

C2.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/openWorld/destructive and non-idempotent behavior, so the safety profile is covered. The description adds genuinely new context the annotations do not: the operation is paid ($0.002 USDC via x402), which is critical for an agent deciding whether to call it. It still omits latency, quality tradeoffs, and that repeated calls incur repeated billing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no filler; the core action and cost are stated immediately. It is arguably too terse given the undocumented parameters, but there is no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid inference tool with zero schema coverage and no output schema, the description is under-specified: it does not explain tier semantics, output shape, billing cadence, or failure/retry behavior. An agent has enough to invoke it but not to invoke it well.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% for three parameters, so the description carries the full burden. It mentions models and cost but never explains the 'tier' enum (fast/smart), the 'system' role, or the expected 'prompt' format, leaving all parameters semantically undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Route prompts') and names the concrete models (Llama 3.1 8B / Llama 3.3 70B) plus the paid mechanism (x402). It is clearly distinguished from the unrelated sibling tools, though it never maps the 'tier' enum values to those models, so the model selection logic stays implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this router versus any alternative, and no indication of when to choose 'fast' vs 'smart' tier. The agent is left to infer selection criteria entirely from the model names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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