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Noaa Tides

by io.github.pipeworx-io

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Idempotent

Create a proactive monitoring subscription to a live-data event stream. Returns the new subscription id. Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions). Supported types: "sec_8k" (8-K filings matching ticker + item codes — e.g. items:["5.02"] = officer change), "polymarket_edge" (Polymarket↔Kalshi cross-venue mispricings — params:{topic:"fed"}), "fred_series" (new FRED observations — params:{series_id:"UNRATE"}). Delivery channels: feed (always on — pull via recent_alerts or GET registry.pipeworx.io/alerts.json), and optionally email (set delivery:{email:"you@x.com"}) or sms (delivery:{sms:"+15551234567"} — phone must be verified at /account first; 10/day cap).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesSubscription type.
paramsYesType-specific filter. sec_8k: {ticker:"AAPL", items?:["5.02","1.01"]}. polymarket_edge: {topic:"fed", min_spread_bps?:500}. fred_series: {series_id:"UNRATE"}. patent_grant: {applicant:"Apple Inc."}. clinical_trial: {sponsor?:"Pfizer", condition?:"lung cancer", phase?:"PHASE3"} (sponsor or condition required).
deliveryNoOptional delivery channels in addition to the always-on persistent feed. {email:"you@x.com"} sends a templated alert per fired event. {sms:"+15551234567"} sends an SMS per event — must match the verified phone on the caller's account (verify at https://pipeworx.io/account first; 10/day cap). {webhook:"https://..."} POSTs each event JSON to your endpoint, HMAC-signed — the response includes delivery.webhook_secret (whsec_…) ONCE; verify X-Pipeworx-Signature = sha256 HMAC of "<X-Pipeworx-Timestamp>.<raw body>". Auto-disabled after 10 consecutive failing runs.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnly=false, idempotent=true, and openWorld=true. The description adds valuable behavioral context: auth requirements, feed always-on behavior, sms verification and rate cap, and the fact that the subscription id is returned. It does not mention idempotency explicitly but does not contradict the annotation either. Given annotation coverage, this adds a solid layer of behavioral detail beyond structured fields.

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 every sentence contributes meaningful detail. It is structured logically: purpose/return value, prerequisites, supported types with examples, and delivery channels. Though it could be trimmed slightly (e.g., webhook details are left to schema), the density is justified given the tool's complexity and multi-type nature.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description appropriately mentions the returned subscription id. It covers the main success paths (create, delivery), prerequisites, and rate limits. The webhook channel is only described in the schema, not the description, but that's acceptable since the schema covers it. For a tool with nested objects and multiple subscription types, the description is sufficiently complete.

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%, so the baseline is 3. The description enriches semantics by providing concrete examples like items:["5.02"] = officer change and clarifying delivery channel requirements (verified phone, 10/day cap). This goes beyond the schema's parameter descriptions, which are already detailed, offering additional actionable nuance.

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 opens with a specific verb+resource ('Create a proactive monitoring subscription to a live-data event stream') and clearly distinguishes itself from sibling tools like list_subscriptions and unsubscribe by focusing on the creation act. It further specifies supported subscription types and return value, making the tool's purpose unmistakable.

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 clear context: when to use (for proactive monitoring), prerequisites (OAuth account required, anonymous/BYO cannot persist), and how to consume alerts via feed/email/sms. However, it does not explicitly name alternatives like 'use list_subscriptions to view existing subscriptions' or 'use unsubscribe to cancel,' so it lacks explicit exclusions or alternative references.

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

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