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EDNA — On-Device Human Sensing for AI

edna.submit_proof

Submit the current human proof (score, classification, quantized signals, hash pattern, optional context/reading/process). Consent REQUIRED: scope.mcp === true. Never raw biometrics.

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": {
      "confidence": "<confidence>",
      "classification": "<classification>",
      "consent": "<consent>"
    },
    "name": "edna.submit_proof"
  }
}

Input Schema

NameRequiredDescriptionDefault
consentYes
contextNo
processNo
readingNo
sessionNoTest session id [a-zA-Z0-9_-]{1,64} — sensor bridge and AI client must use the SAME id. Omit to use the X-EDNA-Session header or the "default" session.
signalsNo
timestampNo
confidenceYes
hashPatternNo
classificationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses consent requirements and the prohibition on raw biometrics, and it enumerates the payload, but it does not explain response behavior, error handling, idempotency, or where the submitted proof goes.

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?

The definition is compact and front-loads the action with a parenthetical payload list, followed by two short constraint sentences. There is little waste, though the parenthetical list is dense and could be slightly clearer.

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

Completeness3/5

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

For a 10-parameter tool with nested objects, no annotations, and no output schema, the description is only partially complete. It covers the core action, consent gate, and privacy rule, but omits success/failure behavior, the shape of nested objects, and the role of timestamp and session beyond the schema's own session note.

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

Parameters3/5

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

Schema description coverage is only 10%, so the description must compensate. It maps several parameters to meaning (classification, quantized signals, hash pattern, optional context/reading/process) and clarifies optionality, but it leaves the structure of nested objects like consent, context, process, reading, and signals unexplained, and does not mention timestamp or session.

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?

The description uses a specific verb ('Submit') and names the resource ('current human proof') with an enumerated payload (score, classification, quantized signals, hash pattern, optional context/reading/process). This makes the operation clear, though it does not explicitly differentiate itself from the many sibling get_* tools.

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?

It states a hard prerequisite ('Consent REQUIRED: scope.mcp === true') but offers no guidance on when to use this tool versus alternatives like edna.get_human_proof or other id.* tools. There is no when-not-to-use or context for choosing submit_proof over other proof-related operations.

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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