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Remoteok

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?

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, which the description complements by detailing the fan-out behavior, fallback from GDELT to GNews on rate limits or 5xx, and the USPTO soft-failure. No contradictions; the description adds valuable behavioral context 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?

The description is a single paragraph with no wasted sentences, front-loading usage examples. It could be more structured (e.g., bullet points) but remains concise given the amount of information conveyed.

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 clearly states the return structure: 'structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs'. It also covers constraints (only company type, USPTO soft-failure). For a 3-parameter tool, this is complete and sufficient for an AI agent to understand what to expect.

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 description coverage is 100%, but the description still adds meaning: it explains the 'since' parameter format (ISO date or relative shorthand) and suggests typical values, clarifies 'type' only accepts 'company', and gives examples for 'value'. This adds marginal but useful extra information beyond the schema.

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 the last N days/weeks/months in ONE parallel call' and lists the sources (SEC EDGAR, GDELT→GNews, USPTO). It differentiates from sibling tool 'entity_profile' by directing to use the latter for static profiles. This is a specific verb+resource with clear scope and sibling distinction.

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 description provides explicit usage examples like 'What's new with X' and 'latest on Y', tells when to use (any question about recent changes) and when not to (use entity_profile for static profiles). It also gives parameter guidance: 'Use "30d" or "1m" for typical monitoring'. This is comprehensive guidance.

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
Disambiguation2/5

Several tool clusters have fuzzy boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions through the same routing layer, while polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and bet_research all address prediction-market edges. Even with detailed descriptions, an agent can easily select the wrong variant.

Naming Consistency3/5

Names are uniformly lowercase snake_case and many follow a verb_noun pattern (list_jobs, search_jobs, resolve_entity, validate_claim), but there are numerous noun-first and adjective-first exceptions (entity_profile, recent_alerts, pipeworx_trending, polymarket_arbitrage) plus bare verbs (remember, forget, recall, subscribe). The pattern is readable but not consistently applied.

Tool Count2/5

34 tools is well above the well-scoped range, and the vast majority are not about the server's RemoteOK namesake. The set appears to merge several distinct domains (Pipeworx data research, Polymarket betting, RemoteOK jobs, memory utilities) into one oversized surface, making it feel more like a bundled platform than a focused server.

Completeness4/5

For the dominant Pipeworx/data-research theme, coverage is strong: question answering, grounded verification, entity profiles, comparisons, change feeds, discovery, memory, subscriptions, and citation-based research are all present. The RemoteOK job subset covers list/search/get without obvious dead ends. Minor gaps exist (no direct citation-URI fetcher, no job alert subscriptions), but agents can work around them.