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launches

by io.github.pipeworx-io

Recent Changes

recent_changes
Read-onlyIdempotent

"What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since since), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). since accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesEntity type. Only "company" supported today.
sinceYesWindow start — ISO date ("2026-04-01") or relative ("7d", "30d", "3m", "1y"). Use "30d" or "1m" for typical monitoring.
valueYesTicker (e.g., "AAPL") or zero-padded CIK (e.g., "0000320193").

TDQS

A4.8/5.0
Behavior5/5

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

The description discloses several behavioral traits beyond annotations: data sources (SEC EDGAR, GDELT→GNews fallback, USPTO), fallback logic, rate-limit handling, soft-fail behavior for patents, and return format (changes[], total_changes, citation URIs). This is rich additional context.

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?

The description is dense but every sentence adds value. It is front-loaded with the core purpose, then details sources, parameters, and output. Slightly long but justified given the complexity; not verbose or redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description explains what will be returned (structured changes[] grouped by source, total_changes count, attribution URIs). It also covers key edge cases like patent API sunset and fallback behavior. Complete for the tool's complexity.

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 covers all 3 parameters with descriptions, so baseline is 3. The description adds extra semantics for 'since' by explaining accepted formats (ISO or relative shorthand like '7d', '30d', '3m') and even recommending '30d' or '1m' for typical monitoring. This goes 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 clearly states the tool provides a change feed for a company, with a specific verb ('change feed') and resource scope. It also explicitly distinguishes itself from sibling tool entity_profile by naming it as the alternative for static profiles.

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?

Provides explicit usage context with natural language examples ('What's new with X', 'latest on Y') and gives a clear exclusion: 'Use entity_profile instead when you want the static profile...' This is exactly the type of when-to-use guidance needed.

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

A3.7/5.0
Disambiguation2/5

Several tools have significantly overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all perform data retrieval, with beta currently identical to stable. The polymarket_* family and bet_research also blur boundaries, and discover_tools vs suggest_questions both handle discovery. Despite detailed descriptions, agents are likely to misselect among these overlapping options.

Naming Consistency3/5

All tools use snake_case, but conventions are mixed: some start with verbs (get_launch, search_launches, ask_pipeworx), others are noun phrases (entity_profile, pipeworx_trending), and there are versioned suffixes (ask_pipeworx_beta). While each domain group has internal consistency, the overall set lacks a unified pattern.

Tool Count2/5

35 tools is excessive for a server named 'launches'—only 4 tools (get_launch, get_past_launches, get_upcoming_launches, search_launches) actually relate to space launches. The remaining 31 tools cover unrelated domains like prediction markets, company profiles, and memory, making the count inappropriate and diluting the server's focus.

Completeness2/5

For the claimed launch domain, the set provides only basic list/detail/search operations and lacks useful launch features like filtering by agency, date range, or launch site. More critically, the inclusion of 31 unrelated tools creates a fragmented surface with obvious dead ends—an agent expecting a launch-focused server would find most tools irrelevant.

Resources