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Glama

Zecmon — poll a scan job

seneschal_zecmon_scan_status

Poll a scan opened by zecmon_scan. Returns phase, progress and the notes found SO FAR — notes accumulate during the scan, so you can read them before it finishes. During "detecting-birthday" the response carries the descending backwards window; during "scanning" it carries birthday → tip coverage. Poll no faster than every 1.5s. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesFrom zecmon_scan.
jobTokenYesFrom zecmon_scan — the only credential for this job.
includeNotesNoInclude the per-note breakdown. Default true; set false for progress only.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
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 discloses that notes accumulate and are returned partial, and it describes phase-specific response content (detecting-birthday vs scanning). This is rich, specific behavioral context beyond what annotations would typically 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 compact but dense, with each sentence adding meaningful information: purpose, partial notes behavior, phase-specific response details, polling rate, and cost. It is front-loaded with the primary purpose and avoids fluff.

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?

Without an output schema, the description does a good job explaining what the tool returns (phase, progress, notes) and how that varies by scan phase. It omits a precise response structure, but for a simple polling tool, the provided context is sufficient.

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 schema already provides 100% coverage for all three parameters (jobId, jobToken, includeNotes) with useful descriptions. The tool description adds no additional parameter-specific semantics; it focuses on behavior and response content, so the score is the baseline for high schema coverage.

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 'Poll a scan opened by zecmon_scan' with a specific verb and resource. This clearly differentiates it from sibling tools zecmon_scan (which starts scans) and zecmon_scan_cancel (which cancels them).

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?

It implicitly says to use after zecmon_scan, and explicitly provides a polling interval guideline ('Poll no faster than every 1.5s'). It does not explicitly list alternatives or when not to use it, but the context from siblings and the phrasing make the usage clear.

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

A3.9/5.0
Disambiguation4/5

Tools are grouped by domain (board, private_watch, zecmon) with clear lifecycle separation, but seneschal_list_at_risk_borrowers and seneschal_list_borrowers overlap heavily, and the USDC vs crypto variants of private_watch_create/topup could be confused without careful reading.

Naming Consistency4/5

Most tools follow a seneschal_<domain>_<action> pattern, but verb/noun order varies (get_borrower vs list_borrowers vs board_list) and outliers like seneschal_health and seneschal_q break the pattern.

Tool Count3/5

At 35 tools, the server is definitely heavy, but it covers multiple distinct domains (DeFi data, privacy-chain monitoring, notice boards, payments), so the count is at the high end of reasonable rather than absurdly bloated.

Completeness4/5

Core workflows are well covered: borrower discovery/analysis, liquidations, private watch lifecycle, Zcash scanning lifecycle, board operations, and checkout invoices. Minor gaps like board deletion or watch cancellation exist but are workaround-able.