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agent-receipts-mcp

Issue a signed action receipt

issue_receipt

Generate a cryptographically signed, timestamped receipt to prove an AI agent performed an action, building a tamper-proof audit trail for compliance.

Instructions

Create a cryptographically signed, timestamped receipt proving that an agent performed an action. Call this immediately after any consequential action (approving an invoice, validating a supplier, sending a payment instruction, making a decision affecting a person) to build an audit trail that satisfies record-keeping obligations such as EU AI Act Articles 12 and 26. Pass the action details; if you include a payload it is SHA-256 hashed and immediately discarded — contents are never stored. Returns the signed receipt JSON, which verifies offline.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actorNoIdentifier of the acting agent, e.g. 'agent:ap-bot@acme'
contextNoOptional string key/value context, e.g. {jurisdiction: 'EU', system: 'erp-prod'}
payloadNoOptional action payload (any JSON). Hashed with SHA-256 and discarded, never stored.
summaryYesOne-line human-readable description of what was done
principalNoThe human or organization the agent acts for
action_typeYesMachine-readable action category, e.g. 'invoice.approved' or 'supplier.validated'
payload_hashNoOptional precomputed 'sha256:<hex>' if you hash the payload yourself (hash-only mode)
Behavior5/5

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

With no annotations, the description carries full burden. It discloses that payloads are SHA-256 hashed and immediately discarded (never stored), and that the returned receipt verifies offline. This goes beyond a minimal description and provides key behavioral details.

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

Conciseness5/5

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

Three sentences, front-loaded with the core purpose and no filler. Every sentence provides actionable information, from what the tool does to when to call it and what it returns.

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?

Despite 7 parameters and no output schema, the description covers what the tool does, when to use it, payload privacy, and the return value. It is sufficient for an agent to invoke correctly without additional context.

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 covers 100% of parameters, including the payload hash-and-discard behavior, so the description adds little beyond what the schema already states. The mention of 'action details' is generic and does not enrich parameter understanding.

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 opens with a specific verb+resource: 'Create a cryptographically signed, timestamped receipt proving that an agent performed an action.' This clearly distinguishes from siblings like verify_receipt and export_audit_bundle by focusing on receipt creation rather than verification or export.

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?

It explicitly says 'Call this immediately after any consequential action' and gives concrete examples (approving an invoice, validating a supplier). It does not explicitly mention when not to use or name alternative tools, but the context is strong enough to guide the agent.

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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