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Pipeworx

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

A4.7/5.0
Behavior5/5

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

Discloses important behaviors beyond annotations: returns subscription ID, requires OAuth, delivery channels include always-on feed, SMS has 10/day cap, webhook secret returned once and auto-disabled after 10 failures. No contradiction with annotations (all consistent).

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?

Well-structured with key information front-loaded (purpose, types, delivery). Some redundancy in the delivery section (phone verification mentioned twice) but overall each sentence adds value. Could be slightly more concise.

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 subscription types, nested parameters, delivery channels), the description is comprehensive. Covers prerequisites, rate limits, return value, and behavior of each channel. No output schema, but the described return is sufficient.

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?

Schema coverage is 100% and the description adds detailed semantics: type enum with use-case examples, params object with type-specific structures (e.g., items codes for sec_8k, topic for polymarket_edge), delivery object with validation requirements. Provides far more meaning than the schema alone.

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?

Clearly states the tool creates a proactive monitoring subscription to a live-data event stream and returns a subscription ID. Describes supported types and delivery channels, distinguishing it from related sibling tools like 'unsubscribe' and 'list_subscriptions'.

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?

Explicitly mentions prerequisites (Pipeworx OAuth account, phone verification for SMS) and provides type-specific parameter examples. However, it does not explicitly contrast with alternatives or state when not to use.

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

A4/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, especially the central data access tools like ask_pipeworx, deep_research, entity_profile, and compare_entities. However, the multiple polymarket tools (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) and the similar ask_pipeworx variants could cause confusion, especially for an agent quickly scanning options.

Naming Consistency4/5

Tool names are mostly snake_case and follow a verb_noun pattern (e.g., compare_entities, search_packs, resolve_entity). Some deviations exist, such as pipeworx_feedback, polymarket_arbitrage (starting with a noun), and single-word names like forget and remember, but overall the style is readable and consistent.

Tool Count2/5

With 36 tools, the server feels overly heavy. While the broad domain (structured data across many sources) justifies a large number, the count exceeds the recommended 15–25 range, making it unwieldy for agents to navigate efficiently without extensive discovery.

Completeness4/5

The tool set covers a wide range of domains: company financials, drugs, economics, prediction markets, weather, and even MCP discovery. There are few obvious gaps given the stated purpose, though some areas like social media or international data could be added. Overall, the surface is well-rounded.

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