Skip to main content
Glama

The Committee

by io.github.pipeworx-io

Subscribe to Alerts

subscribe
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?

The description goes well beyond the annotations by detailing prerequisites (OAuth account), per-type parameters, delivery channel constraints (SMS verification, 10/day cap), webhook behavior (HMAC signing, one-time secret, auto-disable after 10 failures), and return value. No contradictions with annotations (readOnlyHint=false, idempotentHint=true, etc.) are present.

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 relatively long but appropriately dense for the tool's complexity. It is front-loaded with the core purpose and return value, then systematically covers types and delivery options. Some redundancy exists between the description and the schema (e.g., type enum examples), but it remains well-organized and earns its length.

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?

The description covers all necessary aspects: what the tool does, supported types with parameter syntax, delivery channels with constraints, authentication requirements, return value, and caveats (SMS cap, webhook auto-disable). Given no output schema, mentioning the return value is critical and handled. This is complete for a tool of this complexity.

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?

Even though schema coverage is 100%, the description adds extensive meaning: it explains each subscription type's parameter format with concrete examples, clarifies required fields (e.g., 'sponsor or condition required' for clinical_trial), and elaborates on delivery channel semantics (SMS must match verified phone, webhook signing secret). This goes far beyond the schema's descriptions.

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 states a clear verb ('Create') and resource ('proactive monitoring subscription to a live-data event stream'), and explicitly mentions the return value ('Returns the new subscription id'). It distinguishes itself from sibling tools like list_subscriptions and unsubscribe by focusing on creation and proactive monitoring.

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 context for use (proactive monitoring, persistent feed) and mentions requirements (OAuth account, verified phone for SMS). It contrasts with pull-based recent_alerts by noting that the feed is always on and can be pulled via recent_alerts. However, it does not explicitly name alternatives or state exclusions, so a small gap remains.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All The Committee toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation3/5

The ask_pipeworx family creates real ambiguity: ask_pipeworx_beta explicitly states it currently matches ask_pipeworx exactly, leaving an agent no principled way to choose between them. discover_tools and suggest_questions also overlap as meta-tools for navigating the catalog, though the remaining tools (five polymarket_* tools, entity tools, subscription lifecycle) are well-delineated by their detailed cross-referenced descriptions.

Naming Consistency3/5

The set is uniformly snake_case with coherent subfamilies (ask_pipeworx*, polymarket_*, pipeworx_*, remember/recall/forget), but it mixes imperative verb_phrase names (validate_claim, resolve_entity, generate_llms_txt) with noun_phrase names (entity_profile, recent_changes, ai_visibility_check), and the_committee_convene breaks the pattern entirely with a full-sentence name. The inconsistency is stylistic rather than chaotic, so it stays readable.

Tool Count2/5

At 32 tools, the set exceeds the 25+ threshold for 'too many' and the breadth is not fully earned: ask_pipeworx_beta is self-admittedly redundant right now, and several tools feel bolted on from unrelated domains (the_committee_convene, generate_llms_txt, scan_dependency, ai_visibility_check). The core data-research and prediction-market scope would be tighter and more navigable at roughly 20-24 tools.

Completeness4/5

The primary domain — authoritative data lookup, entity research, and prediction-market analysis — is covered with no dead ends: query (ask_pipeworx, grounded, deep_research), profile (resolve_entity, entity_profile, compare_entities), track (recent_changes), verify (validate_claim), bet research (bet_research, polymarket_edges, arbitrage, fill_risk, kalshi_spread), subscriptions (subscribe/unsubscribe/list/recent_alerts), and memory (remember/recall/forget) form complete lifecycles. Minor gaps exist only at the periphery: no execution layer for prediction-market trades (research stops at fill-risk advice) and single-tool coverage for the npm/llms.txt/AI-visibility side-domains.

Resources