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Noaa Tides

by io.github.pipeworx-io

Deep Research

deep_research
Read-onlyIdempotent

ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1500 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,743 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a hop field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoHow many facets to research in parallel: quick=3 (single hop), standard=3 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[] scan across findings), thorough=6 (paid; adds a full iterative hop that chases leads + recovers gaps, plus the contradictions[] scan).
questionYesThe research question, in natural language. Broad/multi-part is fine — decomposition is the point.

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With readOnly/openWorld/idempotent annotations already covering the safety profile, the description still adds substantial behavioral context: not open-web, parallel routing, finding packet shape, never-invented gaps[], contradictions[], stable fetchable citations, hop fields, semantic excerpting, latency, and auth/paid-tier conditions. None of this contradicts the 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 long but dense; every block adds operational value, and key auth/alternative guidance is front-loaded. It earns its length, though it is somewhat redundant with the schema on depth semantics and could be tightened.

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?

No output schema exists, so the description carries the return-contract burden; it discharges it by specifying packet fields, gaps[], contradictions[], hop, citation_uri, and fetchability guarantees. It also covers auth, latency, paid tiers, and depth semantics, so nothing needed to call it correctly is missing.

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?

The schema already covers both parameters at 100% with rich enum descriptions, so the baseline is 3. The description adds meaning by explaining depth behavior (standard re-angles gaps, thorough chases leads, multi-step questions resolve in one call) and by framing the question parameter as broad/multi-part, which takes it above baseline.

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 states a specific verb and resource: grounded multi-source research across Pipeworx's structured data catalog, decomposing questions into facets and routing them in parallel. It explicitly distinguishes itself from open-web search and from ask_pipeworx, so an agent can tell it apart from sibling tools.

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?

It gives explicit when-to-use and when-not-to-use guidance: best for broad/multi-part structured-data questions; use ask_pipeworx for single lookups and breaking/current-news topics; and if not signed in, ask_pipeworx works on every tier. This names alternatives and selection conditions clearly.

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

All Noaa Tides toolsInspect
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TDQS

B3.1/5.0
Disambiguation2/5

The 7 NOAA-specific tools (stations, station_metadata, water_level, currents, met_obs, predictions, datums) are clearly distinct, but they are buried among ~31 Pipeworx platform tools with heavy internal overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route factual queries, while polymarket_edges, polymarket_edge_tracker, polymarket_arbitrage, polymarket_fill_risk, and polymarket_kalshi_spread all analyze prediction-market opportunities. An agent cannot easily tell whether the generic question-answering or prediction-market tools are the right choice without reading long descriptions.

Naming Consistency2/5

Most tools use snake_case, but the naming conventions are inconsistent: some use descriptive nouns (stations, datums, predictions), some use noun_verb pairs (water_level, met_obs), and the Pipeworx batch mixes vendor-prefixed names (pipeworx_feedback, pipeworx_trending), bare verbs (remember, forget, recall, subscribe, unsubscribe), and multi-word verbs (generate_llms_txt, scan_competitor_ai_presence, ask_pipeworx_grounded). No predictable pattern unifies the set.

Tool Count1/5

38 tools is far too many for a server named 'Noaa Tides' — only 7 tools relate to NOAA tide/current data, and the other 31 are an unrelated general-purpose data platform (SEC filings, prediction markets, npm packages, AI visibility scanning, memory storage). The overwhelming majority of the surface has nothing to do with the server's stated purpose, making the count and composition a severe mismatch.

Completeness4/5

For the nominal NOAA tides domain, the surface is reasonably complete: station listing, metadata, observed water levels, currents, meteorological observations, tide predictions, and datums cover the core workflows. Minor gaps exist (e.g., no harmonic constituents or extreme water-level statistics tool), but the essential operations are present. The unrelated tools do not fill gaps in the NOAA domain — they are clutter rather than coverage.

Resources