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TunnelMind Data API

receipt_log_sth

P72 RFC 6962 transparency log over the unified receipt ledger (ADR-010). The STH commits to the entire log: tree_size, root_hash (0x + SHA-256), timestamp, and an Ed25519 signature (with key_id and embedded public key) over the RFC 8785 canonicalization of the body. Hashes only — receipt bodies are never on this surface.

Verify offline with scripts/verify-log.mjs sth (zero TunnelMind library code) against the published receipt-signing key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description provides good behavioral context: it explains that the tool returns a commitment (hashes only, no receipt bodies), lists the fields, and mentions offline verification. While it doesn't explicitly state that it is a read-only operation with no side effects, the technical detail sufficiently conveys the tool's behavior.

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?

The description is concise (three sentences) and front-loaded with key information about the log standard and the STH content. It could be slightly trimmed (e.g., the verification script detail might be secondary), but it remains clear and focused.

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?

Given zero parameters and no output schema, the description is fairly complete: it defines what the tool returns, what it excludes, and how to verify offline. It could be more explicit about the output structure or the fact that no input is needed, but overall it provides sufficient context for an AI agent to understand the tool's role.

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?

The tool has zero parameters, so the baseline score is 4. The description does not need to add parameter semantics, and it correctly stays focused on the tool's purpose and output.

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 clearly states the tool provides the Signed Tree Head (STH) of a P72 RFC 6962 transparency log over the unified receipt ledger. It specifies the exact data fields (tree_size, root_hash, timestamp, Ed25519 signature) and distinguishes itself from siblings by noting that receipt bodies are not included, implying this is for the log's commitment rather than proofs.

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 implicitly tells when to use this tool (to get the STH) and hints at alternatives by mentioning that receipt bodies are never on this surface and that offline verification uses a separate script. However, it does not explicitly contrast it with siblings like receipt_log_inclusion_proof or receipt_log_consistency_proof, leaving room for clearer usage boundaries.

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

B3.3/5.0
Disambiguation2/5

Many tools overlap in purpose, such as cross_lens_verify, cross_lens_lookup, profile_entity, and preflight_should_i_act, which all return node verdicts with subtle differences. Sigil verification tools and receipt-related tools also have similar names and require deep reading to distinguish.

Naming Consistency3/5

The tool names are mostly readable, but the pattern is mixed: some use verb_noun (get_domain, create_subscription) while others use domain prefixes (sigil_*, ghostroute_*, intel_*). Within each domain, naming is consistent, but the overall style lacks uniformity.

Tool Count1/5

With 90 tools, this server is extremely overloaded. Even for a multi-purpose data API, the sheer number overwhelms and makes navigation difficult, far exceeding the typical well-scoped MCP server. The count is an extreme mismatch for the apparent scope.

Completeness4/5

The tool surface is very comprehensive, covering tracker lookup, cross-lens verification, receipts, compliance, subscriptions, tasks, intel probes, and more. Minor gaps exist, such as no batch cross-lens verification, but core workflows are well covered.

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