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Jwt

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

A4.6/5.0
Behavior5/5

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

The description goes beyond annotations, disclosing details like return value, account requirements, per-type parameter usage, delivery channel specifics (e.g., phone verification, 10/day cap, webhook secret, auto-disable after failures). No contradictions 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.

Conciseness4/5

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

The description is long but well-structured, front-loading the main purpose. Every sentence adds value, though some redundancy exists (e.g., 'persist subscriptions' and 'always-on persistent feed'). Overall efficient.

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?

The description covers the return value, constraints, and usage examples for all types and delivery channels. It does not explicitly address error handling but is sufficient given no output schema. Could mention idempotency behavior, but not critical.

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?

Input schema coverage is 100%, but the description adds significant meaning: it explains each type's param structure with examples and delivery options with constraints. This enriches the schema and helps correct invocation.

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 creates a proactive monitoring subscription to a live-data event stream and returns the subscription ID. It distinguishes itself from siblings 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 implies when to use (to set up ongoing monitoring) and mentions requirements (Pipeworx OAuth account, verified phone for SMS). It doesn't explicitly list when not to use or alternatives, but the context is clear.

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

All Jwt toolsInspect
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TDQS

A3.8/5.0
Disambiguation2/5

Multiple tools have unclear boundaries. ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language queries to the same underlying catalog, with ask_pipeworx_beta currently documented as identical to ask_pipeworx. The Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk) also overlaps in purpose, leaving an agent to parse fine-grained differences before selecting.

Naming Consistency3/5

All tool names use snake_case and several share recognizable prefixes (ask_pipeworx_*, polymarket_*), which helps readability. However, the verb/noun order is inconsistent—compare_entities vs entity_profile, bet_research vs deep_research, scan_competitor_ai_presence vs ai_visibility_check—and bare verbs like remember, forget, and subscribe mix with noun-first names.

Tool Count2/5

32 tools is well above the 25-tool threshold for a coherent set. The bloat is worse because the server is named 'Jwt' but only one tool relates to JWT; the rest cover unrelated domains such as data routing, prediction markets, memory, subscriptions, and npm scanning, so the count is neither scoped to the server's name nor internally cohesive.

Completeness2/5

For a server named 'Jwt', the surface is severely incomplete: only decode_jwt is present, with no sign, verify, encode, or refresh tools, so common JWT workflows dead-end. Even when judged as a general Pipeworx data toolkit, the mismatch between the server name and the actual tool surface creates a significant gap for agents expecting JWT functionality.

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