Skip to main content
Glama

sign_action

Create signed audit records for AI agent actions, with compliance mode for hash-only wire envelopes.

Instructions

Create a signed audit record for an AI agent action.

Args:
    agent_id: The agent performing the action
    action_type: Type of action (e.g. "data:read", "api:call")
    action_id: Unique identifier for this action
    payload: Optional JSON payload describing the action details
    compliance_mode: When True, mint a Compliance Receipt by sending the
        hash-only wire envelope (hash + hash_algo + payload_size). Requires
        payload to be supplied so the cloud can resolve the payload_digest
        object form.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idYes
action_typeYes
action_idYes
payloadNo
compliance_modeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the burden. It explains the compliance_mode behavior in detail but does not disclose other behavioral traits like idempotency, side effects, or error conditions. It clearly states it creates a record, implying a write operation.

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

Conciseness3/5

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

The description uses a docstring format with an Args list, which is structured but somewhat verbose. The main purpose is front-loaded, but the parameter explanations could be more concise. It is adequate but not highly efficient.

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?

Given the tool has 5 parameters (3 required) and an output schema, the description covers the essential behavior. It explains the optional payload and the compliance_mode dependency. However, it does not describe the output format, which is partially mitigated by the presence of an output schema.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It explains all five parameters: agent_id, action_type, action_id, payload, and compliance_mode, with a detailed explanation of compliance_mode. This adds significant meaning beyond the schema's type and default values.

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 clearly states 'Create a signed audit record for an AI agent action,' which specifies the verb and resource. It distinguishes from siblings like 'complete_action' or 'check_policy' by focusing on signing, but does not explicitly differentiate from similar logging 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?

No guidelines are provided on when to use this tool versus alternatives. The description does not mention prerequisites, when not to use it, or suggest other tools for related tasks.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jagmarques/asqav-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server