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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=true, idempotentHint=true, and destructiveHint=false. The description adds substantial behavioral context: fans out to multiple sources in parallel, GDELT→GNews fallback mechanism, USPTO soft-fail, return structure (changes[] grouped by source, total_changes count, pipeworx:// URIs). This goes well beyond what annotations provide.

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 a single paragraph but packs in all essential information without redundancy. It is front-loaded with example query patterns, which is helpful. Slightly long but every sentence earns its place; a minor structure improvement could break into sections, but current form is 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 tool's complexity (multiple sources, fallback behavior, two input formats for 'since'), the description covers all needed context: what sources are queried, how fallbacks work, return structure, and explicit cross-reference to sibling tool. No output schema exists, but the description explains the return format adequately.

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 is 3. The description adds value by explaining 'since' accepts ISO dates or relative shorthand with examples ('7d', '30d', '3m', '1y') and explicitly recommends '30d' or '1m' for typical monitoring. Also clarifies 'value' can be ticker or CIK. This extra semantic context justifies a 4.

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 provides a 'change feed for a company in the last N days/weeks/months in ONE parallel call', with example queries like 'What's new with X'. It specifies multiple data sources (SEC EDGAR, GDELT/GNews, USPTO) and distinguishes itself from the sibling tool 'entity_profile' by noting entity_profile is for static profiles.

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?

The tool explicitly tells when to use it (for 'What's new' type questions) and when to use the alternative ('Use entity_profile instead when you want the static profile'). This clear guidance on tool selection is excellent.

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

Multiple near-duplicate clusters exist: ask_pipeworx, ask_pipeworx_beta (explicitly identical to the stable router right now), and ask_pipeworx_grounded all route through the same 5,767-tool catalog, and six polymarket_* tools overlap heavily in surfacing bet/edge opportunities. The blocklist tools (list, recent, aggressive) are only weakly distinguished by time window and confidence, requiring careful reading to select correctly.

Naming Consistency2/5

Naming mixes several incompatible conventions: bare adjectives/nouns for blocklist tools (aggressive, list, recent), brand-prefixed compounds (polymarket_arbitrage, pipeworx_feedback), verb_noun pairs (check_ip, resolve_entity), and noun phrases (entity_profile, bet_research). The server name 'Feodotracker' appears nowhere in the tool names, and the blocklist cluster uses a completely different style from the data cluster.

Tool Count2/5

At 35 tools, the count exceeds the 25-tool threshold for 'too many', but the deeper issue is that roughly 31 tools serve a general data-lookup/prediction-market platform while only 4 serve the server's stated Feodotracker blocklist purpose. The count reflects two unrelated products merged into one MCP server rather than a well-scoped tool surface.

Completeness2/5

For the named Feodotracker domain, the surface is thin: list/check/recent cover basic blocklist access but miss historical lookups, per-entry threat intel, or export formats that a botnet tracker would need. For the data-lookup domain the 31-tool suite is impressively complete, but the two domains don't form a coherent whole—each leaves the other's lifecycle half-served.