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Nuraveda

@qed-proof/mcp

by Nuraveda

Get the public log's signed tree head

get_log_head
Read-onlyIdempotent

Fetch QED Proof's signed Merkle log head with log ID, tree size, root hash, timestamp, signature, and latest on-chain anchor, verifying the signature against published keys.

Instructions

Returns the signed tree head of QED Proof's public Merkle log: the log id, the number of entries (tree_size), the root hash, when it was issued, and the Ed25519 signature, plus the latest on-chain anchor (chain, transaction hash, tree size and block) when one has landed. The signature is checked against the issuer's published poaw-keys.json and the result says whether it verifies. Needs no API key and reads only public data. It checks the head's signature, not that the head extends an earlier one; a consistency proof does that.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.1

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing auth requirements (no API key), data scope (public only), an active verification step against poaw-keys.json with an explicit verifies/not result, and the precise limitation of what is not checked (no extension/consistency verification). This is exactly the kind of behavioral detail annotations alone cannot convey.

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-loads the return payload, then adds auth and verification caveats in a tight sequence. Slightly dense with a long first sentence listing many fields, but every clause (no API key, verification source, consistency-proof caveat) earns its place.

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 carries the full burden of explaining return values and does so field by field, including the conditional anchor. It also states the verification outcome, leaving no ambiguity about what a caller receives or what it does not guarantee.

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?

Zero parameters, so per the rubric the baseline is 4. The description correctly describes a no-argument call and spends its words on return content instead, which is the right trade-off.

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 ('Returns the signed tree head of QED Proof's public Merkle log') and enumerates the exact payload fields: log id, tree_size, root hash, issued time, Ed25519 signature, and on-chain anchor. An agent immediately knows this is a read of the log's signed head, distinct from receipt/verdict/claim 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?

Clarifies context well: no API key needed, public data only, and the anchor is 'the latest on-chain anchor ... when one has landed.' It also draws a boundary against a consistency-proof check ('It checks the head's signature, not that the head extends an earlier one'), though it doesn't name a sibling tool that performs that check.

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