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ledger_verify

Verify the hash-chain integrity of a ledger log, returning ok=true, ok=null, or ok=false with the exact line of the first break. Use strict=true to treat any unchained row as a hard failure.

Instructions

Verify the hash chain over the log. Returns a three-valued verdict: ok=true means EVERY row verified; ok=null means no break was found but unchained prechain rows were skipped UNVERIFIED (verified_scope='bounded_prechain_skipped' — treat as not-green); ok=false names the exact line of the first break (edit, deletion, reorder). Pass strict=true to make any unchained row a hard failure instead of a skip.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
strictNoTreat ANY unchained row as a break (closes the fabricated-legacy-prepend hole). Default false: unchained rows before the first chained row are skipped, counted in `prechain`, and cap the verdict at ok=null.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.7.1

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and handles it well. It discloses the three-valued verdict, the subtle ok=null case where prechain rows are skipped unverified, the verified_scope value, and exactly what strict=true changes. This is rich behavioral disclosure beyond 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.

Conciseness5/5

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

The description is two tightly packed sentences with no filler. The core action is front-loaded, and every clause earns its place by explaining verdict semantics, edge cases, or the strict flag.

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 there is no output schema, the description fully covers return values, the three verdict states, the prechain edge case, and the strict parameter. The behavior is sufficiently complete for an agent to call and interpret the tool correctly.

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?

Schema description coverage is 100%, so the baseline is 3. The description largely repeats the strict parameter semantics already present in the schema, adding only the phrase 'hard failure instead of a skip.' This adds little meaning beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: 'Verify the hash chain over the log,' and goes on to detail the exact verdicts returned. It does not explicitly distinguish itself from the sibling tool verify_peer_ledger, although the focus on local 'log' semantics and prechain behavior provides reasonable differentiation.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool—when hash-chain verification is needed—and explains the strict=true opt-in for stricter behavior. It does not explicitly name alternatives or state when not to use this tool over verify_peer_ledger, so it falls short of a 5.

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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