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jasonwu001t

marketlens-mcp

by jasonwu001t

Corporate actions

reference_corporate_actions
Read-onlyIdempotent

Fetch processed corporate actions by ticker, CUSIP, type, or process-date range; access dividends, splits, mergers, and more, with large results stored for SQL querying via result_id.

Instructions

Processed corporate actions, one row per action with action_type (16 types: dividends, splits, mergers, spin-offs, name changes, ...): process, ex, record, payable and effective dates, cash rate per share (USD), old/new ratio legs, related tickers; columns that do not apply to a type are null (not_applicable). Filter by tickers, CUSIPs, types and process-date window (default today). Large results are stored, not shown: you get a result_id to query with results_query.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoLast process date (Alpaca's default: today).
idsNoSpecific action ids (no other filter).
startNoFirst process date (Alpaca's default: today).
typesNoAction types; omit for all.
cusipsNo
tickersNo
page_tokenNoContinue a truncated fetch: the page_token from the previous response's pagination.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive/openWorld, so safety is covered. The description adds non-obvious behavior: sparse columns are explicitly null rather than omitted, and oversized results are persisted server-side with a returned result_id. Those are genuine operational traits beyond the annotations.

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?

One dense paragraph, front-loaded with what a row looks like before moving to filtering and the truncation/pagination escape hatch. Every clause carries information; slightly long but no filler.

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 no output schema and 7 optional params, the description does the heavy lifting on return shape (columns, null handling) and the result_id handoff to results_query. Complements the schema's page_token note; nothing critical is missing, though the relationship to the announcements sibling remains unexplained.

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?

Schema coverage is 71%, and the description adds semantics the schema lacks: the domain meaning of the five date columns, that cash rate is per-share USD, that ratio legs are old/new, and that non-applicable columns are null/'not_applicable'. This meaningfully extends the schema's terse parameter docs.

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?

States a specific verb+resource ('Processed corporate actions, one row per action') and enumerates the returned fields (action_type, dates, cash rate, ratio legs). It does not name the near-sibling reference_corporate_action_announcement, so an agent can't distinguish this from the announcement feed on description alone, but the 'processed' framing implies the distinction.

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?

Explains filtering dimensions (tickers, CUSIPs, types, process-date window, default today) and the follow-up path when results are large (result_id → results_query). No explicit when-not-to-use or sibling routing, but the triggering context is clear.

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