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Glama

audit_entries

Read the PROVE ledger to see who changed what and when, including guest configuration changes and other audited actions, newest first. Filter by action, target, or caller.

Instructions

READ-ONLY: WHO changed WHAT and WHEN — guest configuration changes and every other audited action, read back from the PROVE ledger.

Newest first. This is how you answer "who changed this guest" or "what has this caller done". matched counts entries passing your filters, total counts the whole ledger, and truncated says so when limit cut rows. An entry with no principal returns null plus a note: the ledger not capturing an identity is a fact about the log, never a claim that nobody was responsible. This READS the chain; audit_verify PROVES it is intact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNewest N entries to return (default 20).
actionNoOnly this exact tool name, e.g. 'pve_guest_config_set'.
targetNoOnly entries against this exact target, e.g. 'vmid=100'.
principalNoOnly entries attributed to this caller id.
mutations_onlyNoOnly entries that changed state.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.31.1

TDQS

A4.8/5.0
Behavior5/5

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

No annotations are supplied, so the description carries the full burden and does so well: it declares READ-ONLY, states ordering (newest first), documents result semantics (matched vs total vs truncated), and adds a subtle caveat that a null principal reflects a logging gap rather than proof of no responsibility. That is exactly the behavioral context an agent cannot infer from the schema.

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

Conciseness4/5

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

Front-loaded with the READ-ONLY signal and the core purpose, and each sentence carries information. It is somewhat dense with capitalized emphasis and em-dash clauses, but nothing is pure filler.

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?

With no output schema, the description steps in to explain return semantics (matched, total, truncated, null-principal behavior) and the read-vs-verify boundary against its sibling. Nothing needed to call or interpret the tool correctly is missing.

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 coverage is 100%, so the schema already documents all five parameters and the baseline is 3. The description still adds meaning beyond the schema — it explains that matched counts entries passing your filters and that truncated signals when limit cut rows, clarifying the effect of the limit and filter parameters.

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?

States a specific verb and resource (reading audited entries from the PROVE ledger) and immediately scopes what it covers — guest config changes and every other audited action. It also explicitly separates itself from the sibling audit_verify ('This READS the chain; audit_verify PROVES it is intact'), so an agent can pick correctly without opening either schema.

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?

Names the concrete questions it answers ('who changed this guest', 'what has this caller done') and names the alternative tool plus the condition that selects it (verify integrity → audit_verify). Both when-to-use and when-to-use-the-other are explicit.

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