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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

A4.5/5.0
Behavior4/5

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

Annotations indicate readOnlyHint=false (write operation), openWorldHint=true (external interactions), idempotentHint=true, destructiveHint=false. The description adds behavioral context: returns new subscription ID, webhook secret returned once, auto-disabled after 10 consecutive failures, SMS cap. No contradictions with annotations. More detail on idempotency semantics would be beneficial but not required.

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 dense yet efficient, with every sentence contributing unique value. It starts with purpose and output, then prerequisites, followed by types and delivery channels in a logical flow. No filler; it balances detail with readability.

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?

For a complex tool with 3 parameters, nested objects, and no output schema, the description covers prerequisites, type-specific parameters, delivery options, and limitations (SMS cap, webhook auto-disable). It mentions the return of subscription ID and webhook secret. Lacking a complete return structure outline, but still highly 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?

All parameters are covered by schema descriptions (100% coverage). The description adds substantial meaning: for each type, it gives concrete examples (e.g., {ticker:'AAPL', items:['5.02']}), explains required vs optional fields, and details delivery channel behavior (e.g., webhook signing, phone verification). This far exceeds 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 clearly states the tool's purpose: creating a proactive monitoring subscription to a live-data event stream and returning a subscription ID. It distinguishes itself from sibling tools like list_subscriptions and unsubscribe by focusing on creation. The list of supported types and delivery channels further clarifies its scope.

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 explicit prerequisites (Pipeworx OAuth account with persist capability) and details on when to use each subscription type with examples. It also explains delivery channel options and their conditions (e.g., SMS requires phone verification, 10/day cap). It could further clarify when not to use this tool (e.g., for anonymous users) but is already strong.

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
Disambiguation3/5

Several families overlap heavily—ask_pipeworx, ask_pipeworx_beta (explicitly identical today), ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions—and the five polymarket_* tools all circle around detecting or trading edges. However, detailed descriptions and distinct scopes (single vs multi-part vs grounded vs claim verdict, scan vs arbitrage vs fill risk) keep most boundaries usable.

Naming Consistency4/5

Names are uniformly snake_case and mostly follow a clear verb_noun or resource pattern (search_articles, compare_entities, list_subscriptions, remember/recall/forget). Minor deviations exist—ask_pipeworx has no underscore and some names are product-prefixed (pipeworx_trending, polymarket_edges)—but the overall pattern is still predictable.

Tool Count2/5

35 tools is well above the 25+ threshold, and the set spans unrelated domains—GDELT news, prediction markets, memory, subscriptions, npm dependency scanning, and llms.txt generation—so it feels like several servers mashed together rather than one coherent scope.

Completeness4/5

As a broad read-only data/research toolkit, coverage is strong: ask_pipeworx routes to thousands of sources, entity/compare/recent_changes/validate cover lookups, memory lifecycle is complete, and subscriptions have create/list/read/cancel. Minor gaps exist—no article-level GDELT aggregates beyond the four news tools and no direct update/delete for llms.txt—but there are no critical dead ends.

Resources