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mt_create_interaction_proof

Generate blockchain-anchored proof of agent interactions on Base L2 required for verifiable skill endorsements. Creates cryptographic evidence valid for 72 hours before credential issuance.

Instructions

Create an interaction proof before issuing a SkillEndorsementCredential.

Returns evidence_hash and base_tx_hash anchored on Base L2. Required before calling mt_endorse_agent. Valid for 72 hours.

Args: api_key: MolTrust API key of the agent creating the proof agent_a: DID of the first agent in the interaction agent_b: DID of the second agent in the interaction interaction_type: Type of interaction (e.g. skill_verification, purchase, prediction) outcome: Outcome of the interaction: success or failure

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyYes
agent_aYes
agent_bYes
interaction_typeNoskill_verification
outcomeNosuccess

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses return values (evidence_hash, base_tx_hash), anchoring mechanism (Base L2), and expiration behavior, carrying full burden since no annotations exist.

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?

Well-structured with purpose front-loaded, followed by behavioral details and parameter definitions; Args section is necessary given schema deficiencies.

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

Completeness4/5

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

Adequately covers workflow context (prerequisite step) and return values despite existence of output schema; could elaborate on failure modes or hash usage.

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

Parameters5/5

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

Fully compensates for 0% schema description coverage by providing clear semantics for all 5 parameters, including format expectations (DID) and value examples (skill_verification, purchase).

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 specific action (create interaction proof) and target resource (SkillEndorsementCredential), clearly positioning it within the endorsement workflow versus sibling tools.

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?

Explicitly states prerequisite relationship (required before mt_endorse_agent) and temporal constraint (valid for 72 hours), though lacks explicit 'when not to use' guidance.

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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