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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.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations (which only indicate readOnly=false, openWorld=true, idempotent=true), the description discloses important behaviors: account persistence requirement, always-on feed delivery via recent_alerts/GET endpoint, email/SMS channels with phone verification and a 10/day cap, and that the feed is always active even without additional delivery channels. It also notes the return value, making the tool's behavior predictable.

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 core purpose and return value, then logically expands into account requirements, type examples, and delivery options. It is longer than average but every sentence contributes valuable information, making it appropriately sized for a tool with multiple subscription types and delivery configurations.

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 the tool's complexity (3 parameters, nested objects, multiple type enums) and the absence of an output schema, the description adequately covers essential aspects: return value (subscription id), account prerequisites, type-specific examples, and delivery behavior. It does not repeat webhook details from the schema but provides enough context for an agent to correctly invoke the tool.

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 input schema already provides 100% coverage with detailed descriptions for each parameter and nested properties. The description adds concrete examples (e.g., 'items:["5.02"] = officer change') and clarifies delivery channel semantics (feed always on, optional email/sms), going slightly beyond the schema by illustrating real usage scenarios.

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 with a specific verb and resource: 'Create a proactive monitoring subscription to a live-data event stream.' It also specifies the return value ('Returns the new subscription id') and distinguishes itself from sibling tools like list_subscriptions and unsubscribe by focusing on creation.

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 for use, including the prerequisite that 'Requires a Pipeworx OAuth account (anonymous + BYO cannot persist subscriptions)' and details supported types with examples (e.g., sec_8k, polymarket_edge, fred_series). It implies when to use the tool but does not explicitly name alternatives or when-not-to-use conditions beyond the account requirement.

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
Disambiguation2/5

Multiple tools are near-duplicates: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded share nearly identical routing, with beta explicitly described as currently identical to stable. The six Polymarket-related tools also form a dense cluster with subtle boundaries, and discover_tools/suggest_questions overlap in onboarding purpose.

Naming Consistency4/5

Most tools follow a clear snake_case verb_noun pattern (check_password, resolve_entity, compare_entities, list_subscriptions), and family prefixes like ask_pipeworx_* and polymarket_* are applied consistently. Minor deviations exist (ai_visibility_check, pipeworx_trending), but the overall convention is predictable.

Tool Count2/5

32 tools is well past the 25+ threshold and the set feels bloated: several ask_pipeworx variants and Polymarket scanning tools could be consolidated, and unrelated utilities (check_password, scan_dependency, generate_llms_txt) are mixed into what is otherwise a data-research platform. The broad scope does not justify this many top-level entry points.

Completeness4/5

The main data-research workflow is well covered: routing, grounded verification, deep research, entity resolution/profiles, comparisons, recent changes, discovery, and feedback are all present. Memory and subscription lifecycles are also complete; minor gaps remain such as the lone password tool lacking generation or breach-checking companions, and no direct raw-fetch tool, but these are workable.

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