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mcp-server

by io.github.tickerbot

tickerbot_subscribe_events

Create an event-trigger webhook: fires when NEW events land — dividends, splits, insider filings, analyst actions ("every split in my universe", "Goldman downgrades on large caps"). TWO composable filters: q filters the event's TICKER STATE (market_cap > 1e10); event_q filters the EVENT CONTENT in the /v2/events grammar (payload->>'firm' = 'Goldman Sachs'). Paid plans (webhook slots). Deliveries carry event: "events.fired" with an events array. Latency = ingest cadence: analyst ≤1h, corporate kinds daily — NOT sub-minute like state webhooks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoOptional row-STATE filter evaluated against the event's ticker at fire time, e.g. market_cap > 1e10.
nameNoDisplay name.
kindsYesComma list of kinds to fire on — any of: dividend, split, insider, analyst (e.g. "split,analyst"). NOTE: no enum here on purpose — a scalar enum would reject multi-kind values.
channelNoDelivery channel.
event_qNoOptional event-CONTENT filter over (ticker, ts, kind, payload jsonb) — only those four identifiers, e.g. payload->>'firm' = 'Goldman Sachs' AND payload->>'action' = 'downgrades'.
tickersNoScope to specific tickers (comma list, max 50). Mutually exclusive with universe; omit both for all tickers.
universeNoScope to a universe slug (top_10, top_100, or a saved one).
device_idNoRegistered device id from the mobile app (channel mobile_push).
target_urlNoHTTPS delivery URL. Omit for in-app delivery.
discord_urlNoDiscord incoming-webhook URL (channel discord).

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well by disclosing the event trigger behavior, filter semantics, delivery payload structure, latency, and paid plan requirement. It does not detail every side effect but covers the key behavioral aspects.

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 front-loaded with the core purpose and each of the five sentences adds valuable information (filters, delivery, latency). It is longer than the two-sentence ideal but remains efficient and free of fluff.

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?

For a tool with 10 parameters, no output schema, and no annotations, the description provides a solid overview of capabilities, payload, and latency. It relies on the schema for parameter details but covers enough behavioral and use-case context to be considered complete.

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?

Although the schema covers 100% of parameters, the description adds critical meaning by distinguishing q (ticker state filter) from event_q (event content filter) and providing examples in the /v2/events grammar. This goes beyond the schema descriptions, warranting a score above the baseline 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool creates an event-trigger webhook for new events, listing specific event types and examples. However, it does not explicitly distinguish this from sibling tools like subscribe_ticker or create_webhook, so it falls short of the highest clarity bar.

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 on when to use this tool (for new event notifications) and includes a latency caveat contrasting with state webhooks, which implicitly guides tool selection. It does not explicitly name alternative tools or state when not to use this tool, but the guidance is clear.

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
Disambiguation4/5

Most tools target distinct resource-action pairs, but get_ticker and get_ticker_history overlap (both return a single historical row via asof), and the four subscribe_* tools are thin wrappers around create_webhook, creating some ambiguity. Detailed descriptions mitigate but don't eliminate confusion.

Naming Consistency4/5

The tickerbot_ prefix and verb_noun pattern are consistent (create_*, get_*, list_*, delete_*, update_*), but subscribe_* deviates from create_* for webhooks, and scan/search_news are bare verbs. Overall predictable.

Tool Count2/5

35 tools is excessive for the domain; many could be consolidated (e.g., four subscribe_* variants into a single parameterized webhook creator, get_ticker/get_ticker_history into one). The breadth of data types justifies some volume, but this exceeds the 25-tool threshold for coherence.

Completeness5/5

Full lifecycle coverage for universes, custom signals, and webhooks; extensive read-side for tickers, series, bars, events, news, and scans. No critical dead ends: anything creatable can be updated/deleted/tested, and data lookups have appropriate query tools.

Resources