TunnelMind Data API

get_receipt

Returns metadata for a TunnelMind surveillance receipt — a signed document proving that a specific user's surveillance exposure was observed, measured, and recorded at a specific time. Does NOT return the receipt's signature (anti-phishing protection). To verify a receipt's content integrity, use verify_receipt with the hash and signature from the receipt document itself.

Use this tool when:

You have a receipt ID and want to confirm it was genuinely issued by TunnelMind.
You need the issuance timestamp and signing key ID for a receipt.
You want to check whether a receipt exists before attempting content verification.

Do NOT use this tool when:

You have the full receipt document and want to verify it hasn't been tampered with — use verify_receipt instead.

Inputs:

receipt_id (path, required): The receipt ID from the receipt document. Alphanumeric with hyphens, max 128 characters.

Returns:

status: FOUND if the receipt is in the registry.
generated_at: ISO 8601 timestamp of receipt issuance.
signing_key_id: identifier of the Ed25519 key used to sign.
schema_version: receipt schema version.
message: human-readable summary with instructions for content verification.
404 if the receipt ID is not in the registry.

Cost:

Free. No API key required.

Latency:

Typical: <100ms, p99: <300ms.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`receipt_id`	Yes

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations provided, the description fully carries the behavioral disclosure burden. It explicitly states the tool does NOT return the signature for anti-phishing protection, lists return fields, indicates 404 for missing IDs, and discloses cost and latency, providing comprehensive transparency beyond what any schema would reveal.

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 structured with clear sections (purpose, usage, inputs, returns, cost, latency). While it is somewhat long, every sentence provides valuable information. The latency and cost details are beneficial but could be considered supplementary, yet they do not detract from the overall clarity.

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?

For a single-parameter tool with no output schema, the description covers all necessary aspects: detailed return fields, error handling (404), cost, latency, and explicit usage guidance. It is complete enough for an agent to invoke the tool correctly without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description thoroughly explains receipt_id, including its source (receipt document), path location, alphanumeric format with hyphens, and max length. This adds meaningful semantic context beyond the schema's pattern and maxLength constraints.

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 it returns metadata for a TunnelMind surveillance receipt, using a specific verb and resource. It explicitly distinguishes itself from verify_receipt by noting it does NOT return the signature, and explains the difference between metadata and content verification.

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

Usage Guidelines5/5

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

The description provides explicit 'Use this tool when' and 'Do NOT use this tool when' sections, naming verify_receipt as the alternative for verification. This clearly guides the agent on when to select this tool vs. siblings.

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.

Resources

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