TunnelMind Data API

ghostroute_ct_witness

Returns GhostRoute's first-party Certificate-Transparency witness state: the latest signature-verified Signed Tree Head (STH) for every trusted, non-Google CT log TunnelMind independently witnesses, plus a regression scan over our own append-only history. Proof the platform holds its own signature-checked roots rather than reselling crt.sh/certspotter.

Use this tool when:

You want corpus-wide CT witness health, not one cert.
You need to know whether any CT log misbehaved (rewound, forked, or served an STH whose signature did not verify) — a serious trust event.

Inputs:

none.

Returns:

summary: logs_witnessed, verified_logs, unverified_logs, all_verified, total_snapshots, regressions, last_observed_at.
logs[]: per-log latest STH (log_url, log_operator, tree_size, sth_timestamp, root_hash, signature_verified, snapshots).
regressions[]: detected violations — kind is tree_size_rewind, root_fork, or sth_signature_invalid (empty array = healthy).

Latency:

Typical <300ms (KV-cached 5m; the witness worker updates twice a day).

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.7/5.0

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. It discloses detailed behavior: returns specific fields for logs and regressions, lists regression violation kinds, states latency (<300ms), caching (KV-cached 5m), and update frequency (twice a day). It also explains the trust context ('Proof the platform holds its own signature-checked roots'). This is a rich, transparent disclosure.

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 well-structured with clear sections (purpose, when to use, inputs, returns, latency). It is front-loaded with the main function, and every sentence adds value—covering output fields, regression kinds, and performance. No fluff or redundancy.

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?

Despite no output schema, the description fully documents the return structure, including the summary fields, per-log array, and regressions array with their possible kinds. It also covers use cases and performance characteristics, making the tool fully actionable for an agent.

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 and an empty input schema, so the baseline is 4. The description explicitly states 'Inputs: none,' confirming there is nothing for the agent to configure. No additional parameter semantics are needed.

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 opens with a precise verb, 'Returns GhostRoute's first-party Certificate-Transparency witness state: the latest signature-verified Signed Tree Head (STH) for every trusted, non-Google CT log... plus a regression scan.' This clearly states what the tool does and its scope (corpus-wide), and distinguishes it from per-certificate tools with the phrase 'not one cert.'

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 provides an explicit 'Use this tool when' section with two specific conditions: 'corpus-wide CT witness health' and detecting log misbehavior. It also excludes per-certificate use with 'not one cert,' but it does not name alternative sibling tools, so it stops short of a full 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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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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