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audit_chain_verify_live

Verify the integrity of a live audit chain by performing an end-to-end check on the server's full history, returning validity status and break details.

Instructions

Ask a running audit-stream-py instance to walk its own chain end-to-end and report whether it's still intact. This is the canonical compliance answer, covers the FULL server-side history, not just events the agent has in context. Returns the same shape as the local audit_chain_verify tool (valid, checked, first_break_at, reason) but for the live chain. Requires AUDIT_STREAM_URL; returns a structured error otherwise.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses key behaviors: it requires AUDIT_STREAM_URL (returns error otherwise), and it returns the same shape as the local variant. It does not indicate side effects like mutation or rate limits, but the tool is apparently read-only. A small gap: could explicitly state it is a read operation, but the action 'walk its own chain end-to-end and report' implies no state change. Score 4 for mostly transparent.

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?

The description is four sentences, front-loaded with the main action. Each sentence adds value: action, scope, return shape, prerequisites, and error handling. No redundancy or fluff.

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?

Given zero parameters, no output schema, and no annotations, the description covers everything: what the tool does, when to use it (canonical compliance), what it returns (same shape as local), prerequisites (AUDIT_STREAM_URL), and error behavior. It is fully self-contained and sufficient for an agent to use correctly.

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?

The input schema has zero parameters and 100% description coverage by default. The description adds no parameter details (none exist), which is appropriate. Baseline for 0 params is 4, and the description clarifies the tool's behavior beyond the schema, so it earns the baseline.

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 uses a specific verb ('ask', 'walk', 'report') and resource ('running audit-stream-py instance', 'its own chain'), and clearly distinguishes from the sibling tool 'audit_chain_verify' by specifying this is for the live chain. The purpose is unambiguous.

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

Usage Guidelines5/5

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

Explicitly states this is 'the canonical compliance answer' and covers 'the FULL server-side history, not just events the agent has in context', guiding the agent to use this when an authoritative check is needed. Also mentions the requirement for AUDIT_STREAM_URL and error behavior, providing clear usage context.

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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