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Glama

Cloudflare Radar

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. The description adds detailed behavioral context: fan-out to multiple sources, fallback mechanism (GDELT→GNews), and soft-failure of USPTO endpoint. It also explains the return structure (changes grouped by source, total_changes count, citation URIs). No contradictions 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.

Conciseness5/5

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

The description is approximately 120 words, front-loaded with example queries, then covers sources, parameters, output structure, and sibling differentiation. Every sentence serves a purpose with no redundancy.

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, the description explains return format (changes array, total count, citation URIs). It covers fallback behavior, potential failures, and parameter constraints. It also provides a clear contrast with entity_profile. Given the tool's complexity, the description is fully informative.

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%. The description adds meaning beyond the schema: explains the 'since' parameter accepts ISO date or relative shorthand with examples, recommends typical monitoring values, clarifies 'type' only supports 'company', and explains 'value' can be ticker or CIK. This significantly aids correct parameter usage.

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 explicitly states the tool provides a change feed for a company in a time window, lists example queries, enumerates data sources (SEC EDGAR, GDELT/GNews, USPTO), and distinguishes from sibling tool entity_profile. This gives a clear, specific purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on when to use this tool versus entity_profile (static profile). It also recommends typical values for the since parameter ('30d' or '1m'). However, it does not explicitly list all alternative tools or exclusion criteria beyond the sibling comparison.

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

A3.6/5.0
Disambiguation2/5

There are three ask_pipeworx variants that overlap heavily, plus five polymarket_* tools scanning similar market edges, and meta-tools like discover_tools, suggest_questions, and deep_research that blur together. ai_visibility_check and scan_competitor_ai_presence also overlap. The Cloudflare Radar tools are distinct, but they are a small minority in a sea of overlapping data/prediction-market tools.

Naming Consistency3/5

Most tools use snake_case, but the pattern is inconsistent: some are verb_noun (list_subscriptions, resolve_entity, scan_dependency), some are noun_phrase (bgp_leaks, internet_quality, radar_domain_rank), and some use vendor-prefixed naming inconsistently (ask_pipeworx vs pipeworx_feedback vs pipeworx_trending). It is readable but not predictable.

Tool Count2/5

37 tools is heavy for any single server, and the collection spans unrelated domains: Cloudflare Radar, Pipeworx data lookup, Polymarket betting, memory, subscriptions, and npm scanning. The count feels like a bundled platform rather than a focused tool set, and many tools could be split into separate servers.

Completeness3/5

The Pipeworx data-research side is quite complete (ask, grounded, deep_research, entity_profile, compare_entities, validate_claim, resolve_entity, discover_tools, recent_changes), and the prediction-market side has good coverage (edges, arbitrage, fill risk, cross-venue spread, tracking). However, the Cloudflare Radar portion is thin—only six tools cover a service known for many more traffic/attack/outage metrics—and the overall surface has no cohesive domain to judge completeness against.

Resources