Stocklake — AI Stock Intelligence

Get Indicator History

get_indicator_history

Read-onlyIdempotent

Historical daily indicator snapshots for a stock — ideal for charting and trend detection. Returns up to days days of data (max 730, default 90) from the stock_indicator_snapshots collection which is populated daily by the indicator pipeline.

Every snapshot row contains:

recorded_at: ISO date string
price: closing price at snapshot time
rsi: RSI(14) value (0-100)
macd_histogram: MACD histogram value (positive = bullish momentum)
bb_pct: Bollinger Band % position (0 = at lower, 100 = at upper band)
sma20 / sma200: 20-day and 200-day simple moving averages

With full=true, each row also gets:

williams_r: Williams %R (0 to -100; >-20 overbought, <-80 oversold)
ultimate_osc: Ultimate Oscillator (0-100; >70 overbought, <30 oversold)
vix_fix_value: Williams VIX Fix synthetic fear gauge (higher = more fear)
williams_ad_trend: Accumulation/Distribution trend (rising/falling/flat)
td_signal: DeMark TD Sequential signal (BUY_SETUP/SELL_SETUP/BUY_COUNTDOWN/SELL_COUNTDOWN/null)
td_phase: DeMark phase (setup_active/setup_complete/countdown_active/countdown_done/null)
analyst_rating: analyst consensus (buy/outperform/hold/underperform/sell or null)
analyst_target: mean analyst price target or null

Returns {} if fewer than 3 snapshots found. Pro tier only. For informational purposes only. Not financial advice.

Input Schema

TableJSON Schema

Name	Required	Description
`days`	No	Number of days of historical daily indicator snapshots to return (max 730, default 90). Returns {} if fewer than 3 snapshots are found in the window.
`full`	No	False (default) returns only recorded_at/price/rsi/macd_histogram/bb_pct/sma20/sma200 per day — enough for most charting/trend use. True adds the specialized indicators (williams_r, ultimate_osc, vix_fix_value, williams_ad_trend, td_signal, td_phase) plus analyst_rating/analyst_target, which barely change day to day and roughly double response size over a long window.
`symbol`	Yes	Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 3, 2026

addedInput schema / properties / full

Added value: +{
+  "default": false,
+  "description": "False (default) returns only recorded_at/price/rsi/macd_histogram/bb_pct/sma20/sma200 per day — enough for most charting/trend use. True adds the specialized indicators (williams_r, ultimate_osc, vix_fix_value, williams_ad_trend, td_signal, td_phase) plus analyst_rating/analyst_target, which barely change day to day and roughly double response size over a long window.",
+  "type": "boolean"
+}

Changed2 schema fields changedAug 25, 2026

addedInput schema / properties / days / description

Added value: +"Number of days of historical daily indicator snapshots to return (max 730, default 90). Returns {} if fewer than 3 snapshots are found in the window."

addedInput schema / properties / symbol / description

Added value: +"Stock ticker symbol. Also accepts a company name as a fallback when it uniquely resolves to one symbol."

AddedJul 7, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already mark readOnly, idempotent, and non-destructive; the description adds substantial behavioral detail beyond that: source collection, daily population, max/default days, empty-response edge case ('Returns {} if fewer than 3 snapshots found'), full-mode behavior, and access restriction ('Pro tier only'). This is rich transparency.

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 organized with a front-loaded purpose statement followed by scannable field bullets. Minor redundancies like 'daily' appearing multiple times are acceptable given the valuable field-level semantics.

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?

Covers the essential operational details: parameter behavior, defaults and limits, edge-case return, access tier, and full vs. base mode. With an output schema present for return structure, the description is complete for an agent to call this tool correctly.

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?

Schema coverage is 100%, but the description adds meaning beyond the schema by interpreting indicator values ('positive = bullish momentum', '0 = at lower, 100 = at upper band'), explaining the difference between base and full mode, and noting that full mode 'roughly double[s] response size' while some fields 'barely change day to day.'

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: 'Historical daily indicator snapshots for a stock — ideal for charting and trend detection.' The focus on indicator snapshots clearly distinguishes it from sibling price-history or market tools like get_stock_history, even without naming them.

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?

Gives clear usage context: 'ideal for charting and trend detection' and notes 'Pro tier only.' It does not explicitly name alternatives or state when not to use this tool, but the intended use case is explicit enough for an agent to select it appropriately.

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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