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luxalgo-mcp-server

by io.github.LuxAlgo
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Hosted Edge Stats coverage

edge_symbols
Read-only

What the hosted Edge Stats store covers: the symbols, their session calendars, coverage windows, session counts, and when the nightly build last ran. Session statistics (how often a setup actually worked, with sample sizes and confidence intervals) come from the open-source edge-stats engine over free market data. Start here, then edge_presets for the questions you can ask, then edge_report for a result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / context / description
      Previous value: -"Explain why you are calling this tool and how it fits into the user's overall goal. This parameter is used for analytics and user intent tracking. YOU MUST provide 15-25 words (count carefully). NEVER use first person ('I', 'we', 'you') - maintain third-person perspective. NEVER include sensitive information such as credentials, passwords, or personal data. Example (20 words): \"Searching across the organization's repositories to find all open issues related to performance complaints and latency issues for team prioritization.\""New value: +"Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
  2. Added

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already mark this as read-only and open-world, so the safety profile is covered. The description adds useful behavioral context by clarifying that hosted data includes coverage metadata but that session statistics come from the open-source edge-stats engine over free market data, reducing the risk of expecting outcomes this tool cannot provide.

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?

Three sentences each add distinct value: contents, data source/semantics, and usage pipeline. The description is front-loaded with the scope and contains no filler or repetition.

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 a single generic context parameter and no output schema, the description gives enough coverage detail and pipeline context for an agent to decide to call it. It does not describe the return format, but that omission is minor here because the tool's role is clearly a starting overview and the annotations cover safety.

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 only parameter, context, is fully described in the schema with a 15–25 word analytics requirement, so the description is not required to add parameter detail. It adds no extra parameter semantics, but the schema already carries the full burden, so 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 states the tool's resource precisely—what the hosted Edge Stats store covers—and enumerates concrete contents: symbols, session calendars, coverage windows, session counts, and nightly build timing. It also distinguishes itself from the sibling tools by naming edge_presets and edge_report and positioning this as the starting point.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit routing guidance: 'Start here, then edge_presets for the questions you can ask, then edge_report for a result.' This tells the agent exactly when to select this tool relative to its closest siblings, with a clear sequencing.

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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