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vigneshv1cky

AlphaDesk

by vigneshv1cky

calendar_accuracy

Determine which earnings-calendar dates are trustworthy by scoring their historical hits against SEC release records at 1, 3, and 7 days ahead.

Instructions

HOW RIGHT THIS READER'S EARNINGS CALENDAR HAS BEEN, scored against the SEC's record of when each company actually released: one day, three days and a week ahead, over the last days (1-120, default 30).

A measured record of which vendor's dates proved right, rather than a claim about them — worth weighting an upcoming date by. Empty until the calendar has been captured for a while; the capture runs once a day.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.4/5.0
Behavior4/5

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

Even though no annotations are provided, the description discloses key behaviors: the tool is a measurement rather than a vendor claim, and it returns empty results until the calendar has been captured for a while, with a once-daily capture run. This is strong behavioral context, though it doesn't mention output format or potential staleness beyond the empty period.

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 and front-loaded with the core purpose, with a second sentence adding useful context. The uppercase opening is stylistically noisy but not padding, so it remains efficient.

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?

For a tool with one optional parameter and no output schema, the description covers purpose, measurement windows, data availability caveat, and parameter semantics. It stops short of describing the exact return shape, but for this simple metric the provided context is largely sufficient.

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

Parameters5/5

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

The description fully compensates for the 0% schema description coverage by documenting the single `days` parameter: it specifies the valid range (1-120) and the default (30). This adds real meaning beyond the bare integer schema.

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 metric: how accurate the reader's earnings calendar has been, scored against SEC actual release dates. It specifies the comparison windows (one day, three days, a week) and the time range, making the tool's purpose unmistakable and distinct from sibling tools like earnings_calendar.

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 gives a concrete use case: weighting an upcoming earnings date by demonstrated accuracy. It also implicitly warns against using it before enough data is captured ('Empty until...'), but it doesn't explicitly contrast it with sibling tools or state when not to use it.

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