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Regulatory Catalysts

by io.github.pipeworx-io

Pdufa Catalysts

pdufa_catalysts
Read-onlyIdempotent

Companies with disclosed PDUFA dates — the highest-signal binary biotech catalyst. Searches recent SEC EDGAR 8-K filings (keyless) for PDUFA target / goal / action dates and extracts the date and surrounding context. A PDUFA date is the FDA decision date for an NDA or BLA; it is a scheduled binary event that moves biotech stocks. Returns each disclosure with company, ticker, CIK, filing date, form, PDUFA date (ISO when the filing gives a specific day), pdufa_period when the filing discloses only a coarser grain such as "Q1 2027" or "March 2027", a short context snippet, the SEC filing URL, and accession number. A row may carry a period without a date — that is the filing being vague, not a lookup failure. Use for PDUFA date, PDUFA goal date, FDA decision date, upcoming FDA decisions, drug approval catalyst, NDA/BLA decision date, biotech binary event, catalyst by ticker.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of disclosures to return (1–10). Default 8.
queryNoOptional extra term ANDed into the search — a drug or company name, e.g. "obecabtagene" or "Capricor". Omit to search all PDUFA disclosures in the window.
sinceNoStart of the filing-date window (YYYY-MM-DD). Default: 120 days before today.
untilNoEnd of the filing-date window (YYYY-MM-DD). Default: today.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds context about keyless access, the default date window, and explains that a period without a date indicates vagueness, not an error.

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?

The description is well-structured, starting with the core purpose, then method, definition, return fields, edge cases, and use cases. Every sentence adds value without redundancy.

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?

Despite no output schema, the description lists all return fields and explains edge cases. It covers purpose, parameters, and use cases adequately, though the default window for 'since' is already in schema.

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?

Input schema covers all 4 parameters with 100% description coverage, including defaults. The description does not add new semantics beyond what the schema already provides, achieving the baseline.

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 states the tool searches SEC EDGAR 8-K filings for PDUFA dates, defines what a PDUFA date is, and lists the returned fields. It distinguishes from siblings like fda_adcom_calendar by focusing on binary biotech catalysts.

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 provides explicit use cases (e.g., 'Use for PDUFA date, FDA decision date, upcoming FDA decisions') but does not mention when not to use it or compare to alternatives.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but the ask_pipeworx variants (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) and multiple Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, etc.) could cause confusion for an agent selecting the appropriate tool.

Naming Consistency2/5

Tool names mix snake_case and camelCase inconsistently, with no strong verb_noun pattern. Examples include 'ask_pipeworx' vs 'discover_tools' vs 'validate_claim', indicating a lack of naming convention.

Tool Count2/5

33 tools is high for a single server, including many utility tools (memory, subscriptions) that seem peripheral to the core regulatory/data domain. This suggests scope creep and could overwhelm agents.

Completeness4/5

The tool set covers a wide range of regulatory and financial data needs, including company profiles, entity comparison, claim validation, FDA catalysts, and prediction market analysis. Minor gaps exist (e.g., no tool for editing data), but overall it is comprehensive for its stated purpose.

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