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Glama

Figma

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?

Discloses fan-out to multiple sources, fallback behavior (GDELT→GNews), soft-fail for USPTO, accepted date formats (ISO or relative), return format (structured changes with URIs). No contradiction with annotations (readOnlyHint, etc.).

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?

Well-structured and front-loaded with query examples. Slightly verbose but every sentence adds value; could be trimmed without losing key info.

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 no output schema, description explains return format (changes grouped by source, total_changes, URIs). Covers failure modes (rate-limiting, sunset API) and date handling, making it complete for a multi-source change feed tool.

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 100% (baseline 3). Description adds practical usage examples for 'since' (e.g., '30d', '1m') and clarifies 'value' accepts ticker or CIK, enhancing beyond 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?

Description clearly states tool as a change feed for companies, enumerates data sources (SEC, GDELT/GNews, USPTO), and provides query examples. Explicitly distinguishes from 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 when-to-use examples (e.g., 'What's new with X', 'latest on Y') and when-to-use-alternative directive for entity_profile. Also notes limitations like USPTO soft-fail and GDELT→GNews fallback.

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

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded), and the set mixes Figma-specific tools with a large library of data-lookup tools, making it hard for an agent to distinguish when to use which.

Naming Consistency2/5

Naming conventions are inconsistent: snake_case (ask_pipeworx, deep_research), camelCase (get_me, get_file), and mixed underscores (list_comments). There is no consistent pattern across the tool set.

Tool Count1/5

The server is named 'Figma' but has 36 tools, only 5 of which are Figma-related. The remaining 31 are Pipeworx data tools, indicating a severe scope mismatch and unnecessary bloat for a Figma server.

Completeness1/5

The Figma-specific tools lack essential CRUD operations (e.g., no create, update, or delete for files or nodes). The Pipeworx tools, while extensive, are irrelevant to Figma, so the server is severely incomplete for its stated purpose.

Resources