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xkcd

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

A4.6/5.0
Behavior5/5

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

The description discloses important behaviors beyond annotations: requires OAuth account (anonymous/BYO cannot persist), phone verification for SMS, 10/day cap, webhook auto-disable after 10 failures, and the one-time return of webhook signing secret. This adds significant context not present in the annotations.

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 dense yet well-structured, starting with the core action, then requirements, supported types, and delivery channels. It is somewhat long but every sentence contributes meaningful detail without fluff.

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 and delivery options), the description covers requirements, examples, limitations (SMS cap, webhook auto-disable), and retrieval methods. It also mentions the return value, which is essential since there is no output schema.

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 schema already provides detailed parameter descriptions with examples, so the baseline is 3. The description adds extra meaning by explaining item code semantics (e.g., items:['5.02'] = officer change) and clarifying SMS verification and webhook behavior, which are not fully captured in 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 clearly states the tool's purpose: 'Create a proactive monitoring subscription to a live-data event stream' and mentions it returns the subscription id. It distinguishes from siblings like list_subscriptions and unsubscribe by focusing on creation, and enumerates supported subscription types.

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?

It provides explicit context on when to use the tool, including required OAuth account, supported subscription types with examples, and delivery channel options. It mentions how to retrieve feed alerts via recent_alerts or a direct GET URL, but does not explicitly state when NOT to use alternatives.

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 heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, entity_profile, compare_entities, and validate_claim all serve data-lookup purposes with unclear boundaries. The three xkcd comic tools are distinct but are buried under 31 unrelated tools, making selection confusing.

Naming Consistency2/5

Tool names follow no consistent pattern: some use verb_first (get_comic, list_subscriptions), some are nouns (entity_profile, deep_research), some have prefixes (ask_pipeworx_*, polymarket_*), and others are vague (scan_dependency, generate_llms_txt). The mixing of styles across the set makes it hard to predict naming.

Tool Count2/5

With 34 tools and a server name of 'xkcd', the count is wildly disproportionate; only 3 tools relate to comics. Even as a general data-access server, 34 tools is heavy and many are meta-tools (discover_tools, suggest_questions) that add bulk.

Completeness3/5

For the actual Pipeworx data domain, the surface is fairly comprehensive: querying, grounded answers, research, entity profiles, comparisons, validation, subscriptions, and prediction-market analysis are covered. However, there are notable gaps like no fetch-by-URI tool and no xkcd search/list capability, making the set incomplete for its name and slightly incomplete for its inferred domain.

Resources