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Glama

sunrisesunset

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").

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already mark readOnlyHint and idempotentHint, but the description adds substantial behavioral context: fans out to SEC EDGAR, GDELT→GNews with fallback rules, USPTO soft-fail due to API sunset, and the return structure (changes[], total_changes, citation URIs). No contradiction with annotations.

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 long but every sentence earns its place: query patterns, source fan-out, fallback logic, output shape, and sibling differentiation. It is well-structured and free of filler or repetition.

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?

With no output schema, the description thoroughly explains return values and source-specific behavior, including fallbacks and soft-fail. It covers parameters, behavior, and alternatives, making it fully self-contained for the agent.

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 100%, so the schema already documents parameters well. The description adds value by giving concrete examples for `since` ('2026-04-01', '7d', '30d'), clarifying `value` accepts ticker or CIK, and noting `type` only supports 'company'.

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 explicitly identifies the tool as a change feed for a company over a time window, with concrete example queries ('What's new with X', 'updates on Acme'). It clearly distinguishes itself from the sibling entity_profile by contrasting dynamic changes vs. static profile.

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: 'change feed for a company in the last N days/weeks/months' and gives practical guidance on `since` values ('Use "30d" or "1m" for typical monitoring'). It also names an alternative tool: 'Use entity_profile instead when you want the static profile...', clarifying when not to use this tool.

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
Disambiguation4/5

Most tools have distinct purposes with detailed descriptions, but there is overlap among closely related Polymarket tools (e.g., bet_research, polymarket_edges, polymarket_arbitrage) and between ask_pipeworx and ask_pipeworx_grounded, which could cause misselection.

Naming Consistency3/5

Tool names mix verb_noun, noun_verb, and descriptive phrases inconsistently (e.g., get_times vs listen_subscriptions vs bet_research), and while many use underscores, conventions vary, making patterns hard to predict.

Tool Count3/5

With 32 tools, the server feels overloaded, covering distinct domains (sunrise, Pipeworx, Polymarket, memory, subscriptions) under one name, making it a 'Swiss army knife' rather than a focused toolset.

Completeness2/5

The server name suggests a narrow domain (sunrise/sunset) but only 2 of 32 tools address it, ignoring related weather data. While other domains are covered, operations lack depth (e.g., no subscription updates, no memory search).

Resources