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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

A4/5.0
Behavior4/5

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

Beyond annotations (readOnlyHint=false, idempotentHint=true), the description adds valuable behavioral context: requires OAuth, returns subscription id, details type-specific params, and notes SMS caps and phone verification. It could clarify idempotency given the annotation, but overall adds significant transparency.

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 front-loaded with the main purpose and efficiently covers key details. While slightly lengthy, each sentence earns its place. A minor trim could be made, but overall structure is clear.

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

Completeness3/5

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

Given the tool's complexity (3 params, nested objects, 5 enums, no output schema), the description covers authentication, return value, and most delivery modes. However, it misses two subscription types and the webhook channel, leaving gaps for an agent to fully understand the parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds examples and constraints (e.g., SMS cap) for three of the five enum types but omits 'patent_grant' and 'clinical_trial' and omits the webhook delivery channel. It provides some added value but is incomplete relative to 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 uses a specific verb+resource: 'Create a proactive monitoring subscription to a live-data event stream.' It clearly distinguishes from siblings list_subscriptions, unsubscribe, and recent_alerts by describing the creation action and the resulting subscription id.

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 implies when to use (for proactive monitoring) and provides context like requiring an OAuth account and mentioning alternative delivery mechanisms (feed vs email/sms). However, it does not explicitly exclude alternatives or state when not to use this tool over siblings.

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

A3.7/5.0
Disambiguation4/5

Most tools have distinct purposes despite overlapping domains like prediction markets, but detailed descriptions help agents differentiate. A few tools like `ask_pipeworx` and `deep_research` could be confused without careful reading.

Naming Consistency2/5

Naming patterns are inconsistent, mixing `ask_`, `polymarket_`, `scan_`, `recent_`, `entity_`, etc., with no unifying convention. The server name 'Hash' mismatches the tool set entirely.

Tool Count3/5

32 tools is on the high side for a focused server, but the set covers many areas. The count is slightly above the typical 3-15 range, yet each tool has a clear purpose.

Completeness2/5

The tool set feels like a collection of unrelated utilities rather than a coherent domain. Core hashing functionality is minimal, while other areas like prediction markets are over-represented with gaps elsewhere.

Resources