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Stocklake — AI Stock Intelligence

Get Watchlist

get_watchlist
Read-onlyIdempotent

The caller's Stocklake watchlist (starred symbols from the web dashboard), enriched with live price, technicals, and AI verdict.

Returns:

  • count: number of symbols on the watchlist

  • items[]: each with symbol, name, sector, price, change_pct, rsi, market_cap, analyst_rating, atr_pct, ai_verdict, ai_headline, ai_score (0-100), ai_score_band (Weak/Moderate/Strong/Very Strong), added_at, price_at_add

  • empty items[] if nothing is starred yet — star symbols at stocklake.dev/dashboard

Pro tier only. For informational purposes only. Not financial advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds useful behavioral context: it returns an empty items[] array when nothing is starred, includes a pro-tier gate, and provides a disclaimer. These details go beyond the annotations without contradicting them.

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?

The description is well-structured: a one-sentence purpose, a bulleted list of return fields, and a note on empty behavior and pro tier. It is front-loaded with the key point, uses bullet points for readability, and contains no filler. Every sentence earns its place.

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 zero-parameter tool, the description is fully comprehensive. It details the output structure (including fields, types, and ranges), explains the empty case, specifies the pro-tier requirement, and provides a disclaimer. The output schema further enriches this, but the description itself is sufficient for an agent to call the tool correctly without external context.

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 tool takes zero parameters, and the schema coverage is 100% (empty properties). Since there are no parameters to explain, the description does not need to add parameter semantics. The baseline for no parameters is 4, and the description correctly focuses on the output and usage.

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 opens with a specific verb and resource: 'The caller's Stocklake watchlist (starred symbols from the web dashboard)'. It immediately distinguishes this from the sibling tools (e.g., get_market_movers, get_stocks) by focusing on the personal watchlist. The enrichment details ('live price, technicals, and AI verdict') further clarify the scope.

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 clear context: it is specifically for the caller's own watchlist, and it notes the 'Pro tier only' requirement. It also gives an explicit fallback for the empty case ('star symbols at stocklake.dev/dashboard'). However, it does not name any alternative tools or state when not to use it, leaving the agent to infer that this is the go-to for the watchlist.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct targets—single stock, batch, news, history, insider activity, screener, market pulse, and so on. The closest pairs are get_earnings_calendar vs get_earnings_intelligence and get_market_assessment vs get_market_pulse, which overlap in raw inputs but differ in AI interpretation; the descriptions provide enough clarification to avoid serious misselection.

Naming Consistency5/5

All 17 tools follow a consistent get_<resource> snake_case pattern, with hierarchical names like get_stock, get_stocks, get_stock_news, get_stock_history, and get_stock_research making related resources obvious. There are no mixed naming conventions or vague verb choices.

Tool Count4/5

At 17 tools, the set is slightly above the ideal range, but the scope is broad and each tool has a plausible role in an AI stock intelligence workflow. The convenience aggregations like get_stocks and get_stock_research add some redundancy but remain purposeful rather than bloated.

Completeness5/5

The surface is comprehensive for a read-only AI stock intelligence domain: single-stock fundamentals and technicals, batch lookups, price history, per-stock and market-wide news, insider activity, screening, market pulse, macro assessment, sector intelligence, earnings, signals, and watchlist enrichment. No major operational dead ends are apparent.

Resources