TunnelMind Data API

receipt_log_inclusion_proof

Proves a specific receipt (by unified receipt_id, lens alias, or raw leaf_index) is included in the tree at tree_size (default: the latest STH's). Returns leaf_hash, the audit_path, the recomputed root_hash, and the matching STH. What this proves: the receipt in your hand is byte-identical to the one sequenced into the log — not that the observation inside it was correct (ADR-010).

Verify offline with scripts/verify-log.mjs inclusion <proof.json>.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`tree_size`	No
`leaf_index`	No
`receipt_id`	No

TDQS

A4.4/5.0

Behavior4/5

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

No annotations provided, so description carries full burden. It discloses return values, default behavior (latest STH), and what is proven vs. not. This is transparent for a proof-of-inclusion tool.

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 concise and front-loaded with the main purpose. Two paragraphs efficiently convey functionality, return values, limitations, and offline usage.

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 no output schema and moderate complexity, the description covers return values, default behavior, proof semantics, and references ADR. Lacks error conditions but is fairly complete for the tool's purpose.

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?

Schema coverage is 0%, but description explains purpose of parameters: receipt_id unifies identifiers, tree_size defaults, leaf_index as alternative. Adds meaning beyond the schema, though lacks detailed parameter descriptions.

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 proves a specific receipt is included in the tree, specifying identifiers and what it proves vs. does not prove. It distinguishes from siblings like receipt_log_consistency_proof and receipt_lookup.

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 distinguishes usage by focusing on inclusion proof, but does not explicitly state when to use this vs. alternatives like consistency proof. However, it provides a practical offline verification step.

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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