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luxalgo-mcp-server

by io.github.LuxAlgo
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Newest Market Trackers rows

trackers_latest
Read-only

What the last daily publish added to one dataset — the newest ingestion day's rows (the dumps' latest.json), optionally narrowed by ticker or text. The cheapest way to see what is new: today's insider filings, this week's congressional disclosures, the latest lobbying registrations. Not available for snapshot-only bulk datasets (patents); use trackers_query there.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoOrder by event date (default newest)
textNoCase-insensitive substring over the dataset's name/title fields (member, insider, issuer, recipient, registrant and client, sponsor, assignee, bill title, …); see textPaths in trackers_datasets
limitNoRows to return (default 25, max 100)
whereNoExact field matches by dot path, e.g. {"side":"buy"}, {"member.state":"CA"}, {"code":"P"}, {"formType":"4"}; string comparisons are case-insensitive, arrays match when any element does
offsetNoRows to skip, for paging (default 0)
tickerNoTrading symbol, case-insensitive (e.g. 'NVDA'); matches the dataset's ticker field(s). Only datasets flagged tickerSearchable carry tickers.
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."
datasetYesDataset id, from trackers_datasets

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 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.\""
    • addedInput schema / properties / offset / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / where / propertyNames
      Added value: +{
+  "type": "string"
+}
  2. Added

TDQS

A4.3/5.0
Behavior4/5

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

Beyond the readOnlyHint/openWorldHint annotations, it reveals the underlying data source (the dumps' latest.json), the meaning of 'latest' (last daily publish), and a major availability limitation for patents. It does not detail pagination or return shape, but the annotations already establish safety and volatility.

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 sentences, each adding value: a precise definition, a use-case illustration, and an exclusion with a fallback. The 'cheapest way' phrase is a bit promotional but still communicates intended use.

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 complex 8-parameter tool with no output schema, the description supplies the key usage context, the semantic of 'latest', and the critical patent exclusion. It does not describe result fields, but the schema is thorough and the rows return shape is inferable.

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 100% and each parameter is well documented in the schema. The description only summarizes the ticker/text filters and points to textPaths in trackers_datasets, adding little beyond the 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 states exactly what the tool returns: the newest ingestion day's rows from the last daily publish, optionally filtered by ticker or text. It also distinguishes the tool from the trackers_query sibling by explicitly excluding snapshot-only datasets.

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 a clear use case ('the cheapest way to see what is new') and an explicit when-not-to-use with the alternative: 'Not available for snapshot-only bulk datasets (patents); use trackers_query there.' This is strong routing guidance.

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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