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Check / Advance Bazaar Listing

check_bazaar_listing
Idempotent

Use this as the resumable pipeline driver for a purchased Bazaar Listing Package: call it any time with the listing_key and it performs the most useful next action and reports {state, next_step}. After the customer deploys their kit it runs Coinbase's validator (per-check fixes on failure); once valid, if the endpoint's price is within our auto-trigger bound (~$1) WE fire the indexing settlement from our own funded wallet — money the customer never fronts; above the bound it points at the kit's self-settle script. Finally it confirms the live merchant-feed entry and returns the receipt (settle tx + feed timestamp). Safe to call repeatedly (idempotent; concurrent calls cannot double-spend). After 5 failed attempts a human specialist takes over automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
listing_keyYeslk_… key issued when the package was purchased (required).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
listingNoCurrent listing summary incl. state (paid → kit_delivered → validated → settled → listed).
messageNo
receiptNoPresent once LISTED: settle tx + merchant-feed entry timestamp + feed URL.
next_stepNo
settle_txNoTransaction hash of the triggering settlement, when we fired it.
validationNoLatest Coinbase validator result (preflight checks with per-check fixes), when a validation ran.

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, the description discloses detailed side effects: running Coinbase's validator, per-check fixes, firing indexing settlement from its own funded wallet, pointing to self-settle above a threshold, confirming the merchant-feed entry, idempotency, concurrent double-spend protection, and human escalation after 5 failures. This is rich behavioral context that annotations alone do not provide.

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 dense but purposeful; the first sentence establishes the core purpose, and subsequent sentences unpack the pipeline steps, safety guarantees, and escalation behavior. Every sentence adds value, though the single-paragraph format could benefit from bullet points for easier parsing.

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?

This is a complex multi-step tool with an output schema, and the description covers the full lifecycle: validation, settlement logic, self-settle fallback, feed confirmation, receipt return, idempotency, and failure escalation. It is sufficiently complete for an agent to invoke it safely and understand expected behavior.

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?

The input schema already provides 100% coverage of the single parameter listing_key, including its format and requirement. The description references the key but adds no additional semantic meaning beyond what the schema states, so the baseline 3 is 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 clearly identifies the tool as a resumable pipeline driver for a purchased Bazaar Listing Package, stating its role in advancing through validation, settlement, and feed confirmation. It is distinct from sibling tools like create_bazaar_listing and validate_x402_endpoint, which serve different stages.

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 states to use it any time with the listing_key for a purchased package, providing clear context and implying it is the ongoing driver after purchase. It does not explicitly name alternatives or exclusions, but the specific mention of 'purchased package' and 'resumable pipeline driver' differentiates it from creation/validation tools.

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

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose, with descriptions that prevent confusion. Tools like scan_site and run_site_audit are differentiated by their focus on AI-readiness vs. site quality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, with clear action words like 'scan', 'create', 'get', 'verify'. Even longer names like 'summarize_scan_for_humans' maintain consistency.

Tool Count4/5

22 tools is slightly above the ideal range but justified by the comprehensive scope of the server, covering scanning, analysis, quoting, file delivery, and verification. Some tools like generate_files and get_customer_files could overlap but serve different contexts.

Completeness5/5

The tool surface covers the entire workflow from site scanning to deployment verification, with no obvious dead ends. All necessary operations for making a site agent-ready are present, including edge cases like x402 validation and credential verification.