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verify_log

Verify that the hash-chained audit log has not been tampered with by walking every entry and confirming each hash links to the previous. Use to prove compliance, after manual edits, or as a periodic trust check.

Instructions

Verify that the local hash-chained audit log has not been tampered with, by walking every entry and confirming each one's hash correctly chains to the previous entry (equivalent to auditreach verify-log --json). Call this to prove compliance/audit integrity before sharing the log with a third party, after any manual edit to the log file, or periodically as a trust check -- it does not need to run before every search. This tool is fully read-only: it opens and reads the log file but never writes to it, is idempotent, and produces the same verdict on repeated calls against an unchanged file. Prerequisite: an audit log file must already exist (one is created automatically the first time search succeeds); pointing this at a path with no log file returns a structured failure rather than raising. Parameters: path (optional string; defaults to ./auditreach.log.jsonl in the current working directory if omitted). Example calls: {} (verify the default log); {"path": "./auditreach.log.jsonl"}. Returns a JSON object with success (bool, true only if the entire chain verifies intact) and exitCode (int); on failure error describes the problem, such as a broken hash link at a specific entry index or a missing/unreadable log file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description fully discloses read-only behavior ('opens and reads the log file but never writes'), idempotency, the prerequisite of an existing log file, and the structured failure mode instead of raising an exception. It also explains return values on both success and failure, leaving no behavioral ambiguity.

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 detailed but tightly organized, moving from purpose to usage, safety, prerequisite, parameter format, and return value. No sentence is redundant; each adds necessary information for correct invocation.

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?

The description covers all relevant aspects: what the tool verifies, when to call it, read-only guarantees, prerequisites, parameter semantics, and return values including failure cases. It is self-sufficient for an agent to select and invoke correctly.

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

Parameters5/5

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

Though the schema only shows an optional path with a default of null, the description explains the default value (`./auditreach.log.jsonl`), gives example calls, and clarifies that the path points to the log file. This adds essential meaning beyond the schema.

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 and resource: 'Verify that the local hash-chained audit log has not been tampered with' and explains the method (walking entries and confirming hash chains). This clearly distinguishes it from siblings like search and auth_status.

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?

It explicitly states when to call — 'before sharing the log with a third party, after any manual edit to the log file, or periodically as a trust check' — and clarifies when not needed: 'it does not need to run before every search'. This provides clear usage boundaries relative to the search sibling.

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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