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Verify a Signed Probe Attestation

verify_attestation
Read-onlyIdempotent

Verify a published Ed25519 probe attestation by canonical dataset id or safe relative digest reference, e.g. 'fuelprice' or 'attestations/2026-08-15/fuelprice.json'. L1 checks signature/key validity; optional L2 replays daily heads to a Git-tag anchor; L3 is provided by verify_evidence. Returns levels.L1.signature_valid and levels.L2.satisfied for signature and replay status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
referenceYesDataset id or relative digest reference, e.g. 'fuelprice'.
replay_chainNoReplay daily heads to the newest tag anchor, e.g. true for an auditor.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds behavioral depth by explaining L1 signature/key checks, L2 replay behavior, and the returned fields. No contradiction with annotations.

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?

Three sentences, each with a distinct purpose: main action, verification levels, and return values. No fluff or repetition, and the most important information is front-loaded.

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

Completeness4/5

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

The description covers the tool's purpose, verification levels, return fields, and the L3 alternative. Since an output schema exists, detailed return structure is not required. Annotations cover safety semantics. Minor gap: no explicit statement about idempotence/open-world behavior, but those are already in annotations.

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 coverage is 100% with descriptions and examples for both parameters. The description adds contextual meaning by defining 'reference' as a canonical dataset id or relative digest reference and explaining L2 replay behavior (related to replay_chain), but it does not explicitly map each parameter.

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 specific verb 'Verify' and resource 'published Ed25519 probe attestation', provides concrete examples of references, and distinguishes from sibling tools by explicitly noting that L3 is handled by verify_evidence. This clearly differentiates it from other verification and search tools.

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: this tool performs L1 and optional L2 verification, and explicitly points to verify_evidence for L3, providing an alternative. However, it does not explicitly state when not to use this tool or contrast with other sibling tools beyond the L3 mention.

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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TDQS

A4.4/5.0
Disambiguation4/5

Each tool targets a distinct workflow—search, detail retrieval, freshness checking, licence enumeration, and citation metadata. The only mild overlap is between get_dataset and get_provenance, both exposing metadata, but their descriptions differentiate full health/freshness detail from citation-ready provenance.

Naming Consistency5/5

All tool names follow a clear verb_noun pattern in snake_case: find_, get_, and search_ prefixes are used consistently. Minor stylistic variation between find_by_licence and find_stale does not undermine predictability.

Tool Count5/5

Five tools is well-scoped for a dataset catalog server, covering discovery, inspection, health assessment, licence scoping, and citation. No redundant or excessive tools are present.

Completeness4/5

The core lifecycle is covered: search to find datasets, get_dataset for full detail, find_stale for freshness risk, and get_provenance for citation. A minor gap is the lack of a general list-all or status filter beyond stale, but the domain is narrow enough to work around this.