Synpareia Trust Toolkit

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recording_proof

Export a recording as a verifiable proof bundle. Anyone can verify the hash-linked chain offline using the signers' public keys.

Instructions

Export a recording as an independently verifiable proof bundle.

Returns the full hash-linked chain as JSON. Anyone with the proof and the public keys of the signing parties can verify it offline with no further calls to you or this toolkit:

pip install synpareia
python -c "import synpareia, json; \
    synpareia.verify_export(json.load(open('proof.json')))"

Safe to share the proof bundle — it contains only what you recorded plus signatures. It does not contain your private key.

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": {
      "recording_id": "<recording_id>"
    },
    "name": "recording_proof"
  }
}

Input Schema

Name	Required	Description	Default
`recording_id`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.6.3Jul 6, 2026

TDQS

A4.4/5.0

Behavior5/5

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

With no annotations, the description fully covers behavioral traits: it states the output is JSON, contains a hash-linked chain, is safe to share, does not contain private keys, and can be verified offline. This is comprehensive for an export tool.

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 description is relatively concise, with a slight overhead from the code block, but every sentence adds value. It avoids redundancy and is front-loaded with the core purpose.

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

Completeness5/5

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

Given the tool's simplicity (one parameter, output schema exists), the description covers all necessary aspects: purpose, output format, verification method, and safety guarantees. No further information is needed.

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?

The only parameter, recording_id, is self-explanatory from its name, but the description does not elaborate on it. With 0% schema coverage, the description could add more detail (e.g., format or constraints), but the parameter's simplicity mitigates this.

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

Purpose5/5

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

The description explicitly states the action ('Export a recording'), the resource ('as an independently verifiable proof bundle'), and provides a unique output format. This clearly distinguishes it from sibling tools like recording_list or recording_start.

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

Usage Guidelines4/5

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

The description implies usage for offline verification and provides a code example, but it does not explicitly state when not to use this tool or suggest alternatives among siblings. It gives good context for appropriate use but lacks exclusion criteria.

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