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Glama

Jina Reader

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. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. Description adds valuable context: fans out to multiple sources, fallback logic, soft-fail for USPTO, and return format (structured changes with citation URIs). No contradictions.

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?

Description is somewhat long but each sentence adds value. Front-loaded with example queries. Could be slightly more structured (e.g., bullet list of sources), but no filler words. Effective for an agent.

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?

No output schema, so description explains return values: 'structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'. Covers complex multi-source behavior, fallbacks, and soft-fail. Completely adequate for agent decision-making.

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%, baseline 3. Description adds meaning: explains `type` enum limitation ('Only "company" supported today'), `since` format variants and a recommended value, and that `value` accepts ticker or CIK. Provides practical usage context beyond 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 returns a change feed for a company, covering SEC filings, news, and patents. It uses specific verbs and resources ('change feed', 'fans out to SEC EDGAR...') and distinguishes itself from the sibling `entity_profile` by contrasting static profile vs. windowed changes.

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?

Explicit guidance: 'Use entity_profile instead when you want the static profile...' and recommends typical `since` values ('Use "30d" or "1m" for typical monitoring'). Also describes fallback behavior (GDELT→GNews) and soft-fail for USPTO due to API sunset.

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

A3.8/5.0
Disambiguation3/5

Most tools have clearly distinct roles, but there is notable overlap in the ask_pipeworx family (stable, beta, grounded, deep_research), and ask_pipeworx_beta is explicitly described as currently identical to ask_pipeworx. discover_tools and suggest_questions also both serve as meta-guidance, creating some selection ambiguity. The very detailed descriptions help, but they do not fully remove the risk of misselection.

Naming Consistency3/5

The set mixes verb-first names like compare_entities and validate_claim with noun-first names like entity_profile and polymarket_edges, along with prefix families (polymarket_*, pipeworx_*, ask_pipeworx_*) and bare verbs like forget and search. Everything is snake_case and readable, but there is no single predictable convention across the whole surface.

Tool Count2/5

33 tools for a server labeled 'Jina Reader' is a sprawling surface spanning data routing, prediction markets, memory, subscriptions, and web reading. Even if each tool is individually focused, the count and combined scope feel oversized relative to the server name and the rubric's guidance for well-scoped servers.

Completeness4/5

Each sub-domain has good lifecycle coverage: memory (remember/recall/forget), subscriptions (subscribe/unsubscribe/list_subscriptions/recent_alerts), entity research (resolve_entity/entity_profile/compare_entities/recent_changes/validate_claim), and Polymarket analysis (edges/arbitrage/fill_risk/kalshi_spread). There are minor gaps like no order execution or simple page summarization, but those appear intentionally out of scope, leaving the surface largely complete.

Resources