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audit_event_compose

Compose a governance event for audit streams by assigning event_id, computing canonical hash, and linking to previous hash. Supports 19 event kinds plus 'other'.

Instructions

Build a ready-to-POST audit-stream-py GovernanceEvent: assigns event_id, computes the canonical hash, links to prev_hash (defaults to 64 zeros for event #1). Kind must be one of the 19 declared event kinds (decision_card_drafted, watch_drifted, request_denied, etc., plus 'other').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYes
sourceYes
payloadNo
event_idYes
prev_hashNo64-char hex; defaults to 64 zeros.
timestampNoOptional ISO-8601; defaults to now.
Behavior3/5

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

Describes computation of hash and default behavior for prev_hash and timestamp, but no annotations are present. Missing details on side effects, permissions, idempotency, or error handling. Provides moderate transparency.

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?

Two concise sentences, front-loaded with purpose, no wasted words. Second sentence provides critical constraints. Efficient and well-structured.

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

Completeness2/5

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

No output schema or annotations; 6 parameters with low schema coverage. Description misses source and payload semantics, return value format, validation behavior, and error conditions. Incomplete for the tool's complexity.

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?

With only 33% schema coverage, description adds meaning to event_id (assigned), kind (enum list), prev_hash (default), timestamp (ISO-8601 default), but source and payload remain unexplained. Partially compensates for gaps.

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 clearly states the tool builds a ready-to-POST audit-stream-py GovernanceEvent, with specific operations: assigns event_id, computes hash, links prev_hash. It lists the 19 allowed kinds, distinguishing it from sibling audit and decision tools.

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

Usage Guidelines3/5

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

Implied usage for preparing an audit event before posting, but no explicit guidance on when to use vs alternatives (e.g., audit_event_emit, audit_event_inspect). No exclusions or prerequisites mentioned.

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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