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audit_chain_verify

Verify the integrity of a GovernanceEvent chain by checking monotonic IDs, hash linkages, and self-consistency. Returns validation results with details of the first break if any.

Instructions

Walk an array of GovernanceEvents top-to-bottom and verify the hash chain: monotonic event_id, prev_hash linkage, self-consistency of each event's hash. Returns { valid, checked, first_break_at, reason }, the same shape audit-stream-py's GET /verify endpoint emits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
eventsYes
Behavior4/5

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

With no annotations, the description fully bears responsibility for behavioral disclosure. It describes the verification steps and return shape, clarifying it is a read-only analysis. However, it does not explicitly state it is non-destructive or mention authorization requirements.

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 sentences efficiently convey the action, verification details, and return shape. No redundant information, front-loaded with the core operation.

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

Completeness3/5

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

The description covers the return shape and core action, but omits parameter structure and does not provide examples or edge case behavior. For a verification tool, more detail on the expected input format would improve completeness.

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

Parameters2/5

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

The sole parameter 'events' is an array of objects, but the description provides no additional details about expected structure (e.g., required fields like event_id, prev_hash, hash). With 0% schema coverage, the lack of parameter description forces the AI to guess or rely on external context.

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's action: walk an array of GovernanceEvents top-to-bottom and verify the hash chain, including specific checks (monotonic event_id, prev_hash linkage, self-consistency). It also specifies the return shape, making the purpose distinct and actionable.

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?

No explicit guidance on when to use this tool versus alternatives like audit_chain_verify_live. The description implies use cases by detailing the verification logic but omits when/not-to-use or prerequisites.

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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