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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

A4.7/5.0
Behavior5/5

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

The description reveals important behaviors beyond annotations: account requirement, return of subscription id, delivery channels, SMS cap, webhook auto-disable after failures. This adds rich context to the annotations which already indicate write and non-destructive.

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 fairly concise for the amount of information conveyed. It front-loads the purpose and requirement, then proceeds with type and delivery details. Minor redundancy with schema descriptions could be trimmed, but overall efficient.

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 types, delivery channels, constraints), the description covers all necessary aspects: required account, type-specific parameters, delivery options with limitations, and return behavior. No output schema exists, but the description notes the new subscription id is returned.

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?

With 100% schema coverage, the description still adds significant value by providing concrete examples for each type (e.g., sec_8k items, polymarket_edge topic), constraints on delivery fields (phone verification, SMS cap, webhook HMAC details), and clarification that webhook secret is returned only once.

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 explicitly states 'Create a proactive monitoring subscription to a live-data event stream.' with clear verbs and resource. It lists specific types and distinguishes from sibling tools like list_subscriptions and unsubscribe.

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 states the requirement for a Pipeworx OAuth account and lists supported types with examples. It provides some context for when to use but does not explicitly exclude scenarios or contrast with sibling tools.

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

A3.6/5.0
Disambiguation2/5

Many tools overlap in purpose, such as multiple query tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and multiple prediction market analysis tools (bet_research, polymarket_arbitrage, polymarket_edges). An agent would struggle to select the appropriate tool due to ambiguous distinctions.

Naming Consistency3/5

Tool names are a mix of styles: some follow verb_noun (ask_pipeworx, forget), others use noun_verb (ecfs_docket_filings), and many are short or compound (bet_research, entity_profile). While the ecfs- prefix tools are consistent, the overall set lacks a uniform pattern.

Tool Count2/5

With 35 tools, the count is excessive for a server named after FCC ECFS, as only 4 tools are directly relevant to that domain. The inclusion of many general-purpose data tools makes the set feel bloated and misaligned with the server's apparent scope.

Completeness3/5

For the FCC ECFS domain, the tool set is incomplete (only 4 tools, lacking submission or deletion capabilities). However, as a general-purpose data query server, it covers many sources (SEC, FDA, patents, etc.). The name mismatch hurts the perceived completeness.