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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

A4.5/5.0
Behavior4/5

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

Annotations indicate non-read-only, idempotent, not destructive. Description adds crucial behavioral details: OAuth requirement, type-specific params, phone verification, daily SMS cap, webhook auto-disable. No contradiction with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Concise (~150 words) with front-loaded purpose. Well-structured: first sentence gives core functionality and return, then constraints, type breakdown, and delivery details. Every sentence adds essential information.

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?

For a 3-parameter tool with no output schema and high schema coverage, the description is fully complete. It covers required fields, optional params, constraints, and behavioral nuances, leaving no gaps for an AI agent.

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?

Schema coverage is 100%, but description adds significant value by providing concrete examples (e.g., 'items:["5.02"] for officer change') and explaining delivery channel specifics beyond schema 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 clearly states the verb 'Create', the resource 'proactive monitoring subscription', and specifies the return value 'subscription id'. It distinguishes from siblings like 'unsubscribe' and 'list_subscriptions'.

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?

Explicitly says when to use: for proactive monitoring to live-data event streams. Lists prerequisites (Pipeworx OAuth account), supported types, and delivery channels. Lacks explicit when-not-to-use, but provides sufficient context.

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

The tool set mixes three near-identical ask_pipeworx variants, multiple overlapping prediction-market tools (polymarket_edges, polymarket_arbitrage, bet_research), and three endoflife tools buried among 31 unrelated Pipeworx tools. This makes distinguishing between tools genuinely confusing, especially when several appear to route to the same underlying data.

Naming Consistency3/5

Most names use lowercase snake_case, but the verb-noun pattern is inconsistent: some are verb_noun (list_products, get_product), others noun_noun (polymarket_edges, bet_research), and a few are bare verbs (recall, forget). The style is readable but does not follow a single predictable convention.

Tool Count2/5

With 34 tools, the count is far too high for a server named 'Endoflife'—only three tools actually relate to endoflife.date tracking. The remaining 31 tools belong to a separate Pipeworx platform, making the tool count an extreme over-scoping for the apparent purpose.

Completeness4/5

The endoflife subset is complete: list_products, get_product, and get_cycle cover the full lifecycle of discovering and retrieving release/support timelines with no dead ends. The broader Pipeworx toolkit also appears fairly comprehensive for its own domain, but the mixed set makes it hard to assess a single coherent surface.