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theodor90

form4api-mcp

health_ingestion

Read-only

Check live ingestion health for Form 4 processing freshness, parse-queue backlog, and price-feed staleness. Returns healthy, degraded, or stale status with HTTP 503/200 codes for direct uptime monitoring.

Instructions

Ingestion-death detector — Form 4 freshness, parse-queue health, price-feed freshness. Returns live (uncached) ingestion health: Form 4 processing freshness (stale after 90 minutes during the weekday 06:00-22:00 US Eastern EDGAR activity window, 14 hours outside it), parse-queue health (stale when >50 jobs are pending AND the oldest has waited >45 minutes), and daily price-feed freshness (degraded, never stale, when price bars are >5 days behind). Overall status is "healthy", "degraded" (price feed only), or "stale" (Form 4 or queue). Returns HTTP 503 when stale, 200 otherwise — safe to point an external uptime monitor at directly. No API key or plan required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.9.6

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint=true and openWorldHint=true annotations, the description reveals key live behaviors: the result is uncached, the exact staleness thresholds for each component, the overall status values, and the HTTP 503/200 response semantics. That is strong behavioral transparency.

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?

Though the description is dense, every clause earns its place: thresholds, status logic, HTTP behavior, and authentication requirements are all covered without fluff. The leading 'Ingestion-death detector' immediately orientates the agent.

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 zero-parameter, no-output-schema health utility, the description provides all the context an agent needs to invoke it and interpret the result: what is measured, when it is considered stale, what overall statuses occur, and what HTTP status is returned. Nothing crucial is missing.

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?

The tool takes zero parameters and schema coverage is 100%, so there are no parameter semantics to document. The baseline for a parameterless tool is appropriate here, and the description correctly focuses on behavior instead of parameters.

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 names a precise resource ('Form 4 freshness, parse-queue health, price-feed freshness') and an actionable verb ('detector'/'Returns live ingestion health'). It clearly differentiates this tool from the broader sibling set focused on filings, insiders, or usage by centering on ingestion pipeline health.

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 gives explicit context on when to use the tool: it can be pointed at directly by an external uptime monitor, and it requires no API key or plan. It does not enumerate alternatives or say 'use X instead of Y', but the use case is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.