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My watchlist brief

alphai_watchlist_brief
Read-onlyIdempotent

Summarize the caller's saved AlphAI watchlist in one read. Returns recent news grouped by story, a separate SEC filings section and the next confirmed earnings dates. Manage tickers at https://alphai.io/account/watchlist. Each story names the watched tickers it affects, carries a short summary and links to the article and its original source. Windows use article publication timestamps, not ingestion time; this is a ranked snapshot, not a changes cursor. Events and filings each contain up to limit items, with explicit truncation flags when more exist. Each section groups the newest 500 matching articles, then ranks by relevance, novelty and recency. Narrow hours or open the ticker feed when a section is truncated. Unknown tickers are listed separately. An empty tickers list means the caller has not saved a watchlist. A missing earnings date means no confirmed date is held, not that the company will not report. Available on every tier.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursNoPublication look-back in hours; default 24.
limitNoMaximum stories per section (news and filings).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
hoursYes
eventsYes
filingsYes
tickersYes
window_endYes
generated_atYes
window_startYes
unknown_tickersYes
events_truncatedNo
filings_truncatedNo
upcoming_earningsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and the description adds extensive behavioral detail: publication timestamps vs ingestion time, truncation flags, ranked snapshot semantics, unknown ticker handling, and missing-date semantics. This goes well beyond the structured annotations and gives the agent a precise mental model. 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.

Conciseness3/5

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

The description is front-loaded with the core purpose, but it is long and includes non-essential details such as the account management URL and 'Available on every tier.' While most sentences add behavioral value, the extra operational noise slightly dilutes conciseness, so it earns a 3 rather than higher.

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 two-parameter, read-only tool with a full output schema and rich annotations, the description covers all practical edge cases: truncation, empty watchlist, missing earnings dates, unknown tickers, and ranking behavior. The only minor omission is explicit pagination details, but the output schema and truncation flags cover that, so the description is complete enough.

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 description coverage is 100%, so the baseline is 3. The description adds extra semantics by clarifying that 'Windows use article publication timestamps, not ingestion time' (defines hours) and that 'Events and filings each contain up to limit items' (defines scope of limit). This adds meaning beyond the schema, so a 4 is warranted.

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?

States a specific verb and resource: 'Summarize the caller's saved AlphAI watchlist in one read.' It further clarifies outputs: recent news grouped by story, SEC filings section, and earnings dates, which distinguishes it from sibling tools like alphai_ticker_news or alphai_news_search. The 'caller's saved watchlist' scoping makes the tool's unique role clear.

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?

Provides clear context on when to use this tool: as a one-read summary of the saved watchlist, and explicitly advises 'Narrow hours or open the ticker feed when a section is truncated.' It also clarifies that it is a ranked snapshot, not a changes cursor, which implies it isn't for change detection. It does not explicitly name alternative tools or state when not to use it, so not a perfect 5.

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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