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Glama

Pexels

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 readOnly/idempotent/destructive hints. The description adds valuable behavioral context: fans out to SEC EDGAR, GDELT→GNews fallback (rate-limited or 5xx), USPTO PatentsView sunset causing soft-fail until reactivated, and the return format with pipeworx:// citation URIs. No contradiction.

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 front-loaded with example queries, then packs details on data sources, fallback, and return shape. Every sentence carries information, though the single-paragraph format could be more scannable with bullet points. No wasted words.

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?

Despite having no output schema, the description fully covers return value ('structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'). It also explains edge cases (GDELT vs GNews fallback, USPTO soft-fail) and the 'ONE parallel call' architecture, making the tool well-understood without external references.

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 baseline 3. The description adds extra practical guidance: 'since' accepts ISO date or relative shorthand, recommends 'Use "30d" or "1m" for typical monitoring', and clarifies 'value' examples (ticker or zero-padded CIK). This exceeds the schema descriptions.

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 uses a specific verb and resource: 'change feed for a company in the last N days/weeks/months' and opens with concrete example queries. It distinguishes itself from sibling tool `entity_profile` by contrasting dynamic change feed 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?

Explicit guidance is provided: 'Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.' The description also explains when the tool is appropriate ('What's new with X') and includes fallback behavior that implies usage conditions.

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
Disambiguation3/5

Many tools are clearly from distinct domains (Pexels media, Pipeworx data, Polymarket betting, utility), but within each domain there is significant overlap (e.g., ask_pipeworx vs ask_pipeworx_grounded vs deep_research, or numerous polymarket tools). Detailed descriptions help differentiate, but some tools could still be confused.

Naming Consistency3/5

Naming conventions vary: some tools use verb_noun (ask_pipeworx, compare_entities), others are single-word (photo, video), and some mix patterns (photo_curated vs photo_search). The Pexels subset is consistent, but the overall set includes tools from other ecosystems with different styles.

Tool Count2/5

With 38 tools, the set is bloated for a Pexels server. Only 8 tools are actually Pexels-related; the rest are Pipeworx data query, Polymarket betting, and utility tools. This mismatch makes the count inappropriate for the stated server purpose.

Completeness4/5

For the Pexels domain, the tool set covers search, fetch, and collections for both photos and videos, which is adequate. The unrelated tools add bloat but don't create gaps in the Pexels functionality. Minor missing features like uploads or editorial content are not critical.

Resources