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Glama

Unpaywall

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 indicate read-only, idempotent, open-world. Description adds details on data sources (SEC, GDELT/GNews, USPTO), failure modes (GDELT rate-limited, PatentsView sunset), and return structure. 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.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is front-loaded with examples and use cases. It is detailed but every sentence serves a purpose. Slightly longer than necessary for a concise description, but still effective.

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?

Given the rich annotations, complete schema coverage, and detailed description covering sources, failure modes, and return structure, the description is fully complete for an agent to understand and use the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%. Description adds meaning by explaining accepted formats for 'since' (ISO date or relative shorthand like '7d', '30d'), 'value' (ticker or zero-padded CIK), and enum for 'type'. Provides example usage 'AAPL' and '0000320193'.

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's purpose: 'change feed for a company in the last N days/weeks/months' with concrete examples like 'What's new with X' and 'latest on Y'. It explicitly distinguishes from the sibling tool entity_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 guidance: 'Use entity_profile instead when you want the static profile...' and explains the tool fans out to multiple sources. The context signals and sibling list confirm this is well-differentiated.

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

Several tools overlap in purpose, especially the ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) which all answer factual questions but differ in grounding/depth. The beta version is explicitly identical to the stable one currently, creating confusion. The Polymarket analysis tools also have overlapping scopes, though their descriptions help differentiate them. Overall, most tools have distinct roles but the heavy overlap in the query router cluster makes misselection a real risk.

Naming Consistency3/5

Tool names mix several conventions: bare verbs (remember, subscribe, forget), verb_noun (compare_entities, resolve_entity), noun_phrase (entity_profile, pipeworx_feedback), and a brand-prefixed family (ask_pipeworx*, polymarket_*). While some prefixes are consistent, the overall pattern is inconsistent and not predictable. Names are readable but do not follow a single style.

Tool Count2/5

With 33 tools, the server is heavily over-scoped for its name 'Unpaywall', which implies a narrow open-access search utility. Even though the actual functionality is broad, the tool count is excessive and will overwhelm agents. Many tools (llms_txt generation, dependency scanning, memory) are unrelated to the core data-query function.

Completeness4/5

For the actual domain revealed by the descriptions—a comprehensive data research and prediction-market gateway—the tool surface is quite complete: it covers discovery, retrieval, grounding, entity resolution, comparison, validation, subscriptions, memory, and prediction-market analysis. Minor gaps exist (e.g., no subscription update tool, no direct tool to list all data packs), but agents can work around them. If the domain is strictly 'Unpaywall/open access', it's severely incomplete, but the descriptions clearly indicate a broader scope.

Resources