Skip to main content
Glama

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").

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 (SEC, GDELT/GNews, USPTO), fallback behavior (GDELT preferred, GNews on rate limit/5xx), soft-fail for patents (PatentsView API sunset), and return structure (changes[] grouped, total_changes, citation URIs). Adds significant value beyond 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?

Single paragraph but well-organized: purpose, internal logic, parameter hints, sibling distinction. Every sentence adds value, though slightly dense.

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 complexity (multiple sources, fallback, return format), the description covers key aspects including a temporary API issue. Mention of return structure compensates for missing output schema. No obvious gaps.

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% with detailed descriptions. Description adds examples for 'since' (ISO date, relative shorthand, suggests '30d' or '1m') and mentions ticker or CIK for 'value'. Minor added value.

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 it is a change feed for a company within a time window, listing example queries and explicitly contrasting with entity_profile. The verb 'change feed' and resource 'company' are specific and distinguishable.

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... regardless of window.' Also suggests typical monitoring duration '30d' or '1m'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route to the same 5,714-tool catalog with heavily overlapping purposes, and ask_pipeworx_beta is currently identical to ask_pipeworx. Similarly, bet_research, polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, and polymarket_fill_risk all target prediction-market analysis and could easily be confused by an agent. The two FAA tools (faa_regulation, faa_search) are distinct, but they are buried among a dozen unrelated data-lookup and memory tools.

Naming Consistency4/5

Most tools follow a consistent lowercase snake_case verb_noun or noun_verb pattern (faa_search, resolve_entity, compare_entities, validate_claim, discover_tools, unsubscribe). Minor deviations exist, such as ask_pipeworx and pipeworx_feedback lacking underscores, and the polymarket_* family mixes noun-led names, but overall the naming is readable and predictable.

Tool Count1/5

33 tools for a server named 'Faa Regulations' is a severe mismatch: only 2 of the 33 tools (faa_regulation, faa_search) relate to FAA regulations, with the rest covering general data lookups, prediction markets, SEC filings, memory storage, npm dependency checking, and llms.txt generation. The count is far too high for the stated domain, and most tools do not belong in this server at all.

Completeness2/5

The actual FAA surface is thin: faa_search provides keyword lookup and faa_regulation returns full text or a part's section list, so basic citation-lookup workflows work, but there is no update/amendment tracking, no browse-by-part navigation beyond a section list, and no related aviation data such as NOTAMs or TFRs. The dominant Pipeworx tool family is unrelated to FAA regulations, so an agent using this server for its apparent purpose would hit dead ends quickly.