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puntersedge

by io.github.Propertyscout001
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Bulk dataset catalogue

bulk_datasets
Read-onlyIdempotent

The downloadable Parquet/CSV datasets (closing lines, price paths, results) and which days and months exist. Files are downloaded over REST with your key, never through MCP: GET https://api.puntersedge.online/v1/bulk/{dataset}/{period} (20 credits per day file, 100 per month file). Free. Plan: Business and above.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "bulk_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault
datasetNo

Output Schema

NameRequiredDescriptionDefault
dataYesThe API response, with links and empty fields removed.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive, and the description adds real behavioral facts: no file bytes traverse MCP, authentication is a key against REST, and pricing is 20 credits per day file / 100 per month file. The 'Free. Plan: Business and above.' sentence is ambiguous about what exactly is free versus credit-charged, which keeps it from a 5.

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?

Three compact sentences, front-loaded with what the datasets are, then the access mechanism, then cost/eligibility. The staccato 'Free. Plan: Business and above.' is efficient but reads as a fragment whose referent is unclear, slightly weakening the payoff.

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?

With an output schema present, the return shape needn't be explained, and the mutation/credit/plan constraints are covered. The remaining gap is the optional 'dataset' filter and its valid values, which an agent needs to call the tool without guessing.

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 0% for the single 'dataset' parameter, so the description must carry it. It names candidate dataset concepts (closing lines, price paths, results) and hints at the period segment in the URL, but never states the accepted identifier strings, that the parameter is optional, or what is returned when it is omitted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the resource concretely (downloadable Parquet/CSV datasets: closing lines, price paths, results) and states it reports which days and months exist, so the catalogue nature is clear. The verb is implicit rather than stated ('list/returns'), and it doesn't name a sibling, but the explicit 'files are downloaded over REST, never through MCP' carves out a distinct role from the query-oriented siblings.

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 the actual usage path: this tool reveals availability, then you fetch via GET https://api.puntersedge.online/v1/bulk/{dataset}/{period} with your key. It also gives the plan gate (Business and above) and credit cost, which tells the agent when this is viable. It stops short of an explicit instruction like 'call this first to discover valid period values' and offers no stated alternative/exclusion pair.

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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