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aibtc-mcp-server

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tx_status_deep

Diagnose sponsored transaction lifecycles by correlating sender nonces with sponsor nonces, flagging sponsor nonce gaps, missing mempool entries, and competing RBF txids.

Instructions

Deep diagnostic view correlating sender nonces with sponsor nonces for sponsored transactions.

Reads the sender's local pending txid log and cross-references each entry against the sponsor's mempool to show the full lifecycle of sponsored transactions:

  • Which sender nonce maps to which sponsor nonce

  • Whether sponsor nonce gaps are blocking specific transactions

  • Which pending txids are missing from the sponsor mempool entirely

  • Multiple competing txids (RBF candidates) for the same sender nonce slot

Output per nonce slot: Sender nonce N: - 0xabc (sponsored, sponsor nonce 47) -- BLOCKED by missing sponsor nonces [44, 45] - 0xdef (direct, fee 0.01 STX) -- competing RBF candidate Sender nonce M (0xghi, sponsored) -> sponsor nonce 48 -- pending, no gaps ahead Sender nonce P (0xjkl, sponsored) -> NOT IN SPONSOR MEMPOOL

Use this when check_relay_health shows issues but you need per-transaction clarity. Returns structured JSON with pendingSlots, sponsorMissingNonces, and summary counts.

Tip: call earning_opportunities to see how to put your assets to work.

Input Schema

NameRequiredDescriptionDefault
addressNoSTX address to check. Defaults to the active wallet address.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.77.0

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it explains that it reads the local pending txid log, cross-references the sponsor mempool, and details output per nonce slot including gaps, missing txids, and RBF candidates. It also names the structured return fields (pendingSlots, sponsorMissingNonces, summary counts).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose and usage are front-loaded and useful, but the description is lengthy with elaborate output examples and an unrelated 'Tip: call earning_opportunities' sentence that does not earn 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?

Given the lack of annotations and no output schema, the description is complete enough for an agent to understand the diagnostic behavior and the shape of the returned JSON. It fully covers what the tool does and what to expect.

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

Parameters3/5

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

Schema description coverage is 100% for the single optional address parameter, so the schema already documents it. The description adds no additional meaning about the address parameter, making baseline 3 appropriate.

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 states a specific verb and resource: a deep diagnostic view correlating sender nonces with sponsor nonces for sponsored transactions. It clearly distinguishes itself from check_relay_health by requiring per-transaction clarity.

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?

It explicitly says when to use it ('when check_relay_health shows issues but you need per-transaction clarity'), which implicitly routes aggregate checks to check_relay_health. This is a clear selection rule between 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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