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FinBridge

Oliver Kell Cycle Screener — approximation (FinBridge DB)

screen_kell
Read-only

Screen KR, US and/or TW stocks for an Oliver Kell "Cycle of Price Action" long setup, evaluated on the nightly indicators_latest snapshot (daily corporate-action-adjusted KR prices).

APPROXIMATION: Oliver Kell's method is discretionary — his full cycle (reversal extension, EMA crossback, wedge pop, base-n-break, exhaustion) is a chart read, not a formula. This screener only proxies ONE phase: "a relative-strength leader in an uptrend, riding its short-term EMAs and not over-extended". It will miss real Kell setups and flag stocks that are not.

Conditions (all required):

  • close > 20-day EMA (uptrend, holding the 20EMA)

  • price is 0..'max_ext_pct'% above the 10-day EMA (above support but not exhausted)

  • RS percentile >= 'rs_min' (a leader)

  • if require_ema_stack: 10-day EMA > 20-day EMA (rising short-term stack)

Args:

  • market: 'kr', 'us', or 'all' (default)

  • rs_min: minimum RS percentile 1-99 (default 80; Kell trades leaders)

  • max_ext_pct: max % above the 10-day EMA before treating it as over-extended (default 15)

  • require_ema_stack: require 10EMA > 20EMA (default true)

  • min_vol_avg20: optional minimum 20-day average volume (liquidity filter)

  • min_price: optional minimum close price (avoid low-priced stocks; e.g. 10 for US$, 5000 for KRW)

  • sort_by: rs_pctile|pct_from_ema10|ret_20d|ret_5d|macd_hist|close (default rs_pctile)

  • order: 'asc'|'desc' (default 'desc'); limit: 1-50 (default 20); response_format: 'markdown'|'json'

Returns: {count, market, criteria:{rs_min, max_ext_pct, require_ema_stack}, rows:[{name, source, ticker|stock_code, as_of, close, ema10, ema20, pct_from_ema10, macd_hist, rs_pctile, ret_20d}]}.

Examples:

  • US leaders on EMA support: {market:'us', min_vol_avg20: 500000}

  • Tighter KR leaders near the 10EMA: {market:'kr', rs_min: 85, max_ext_pct: 8, min_vol_avg20: 100000}

Use when: shortlisting momentum leaders riding short-term EMAs (Kell style, approximate). Don't treat a pass as a Kell "buy" — the cycle phase and chart context are discretionary. For the 8-point trend template use screen_minervini; for arbitrary technicals use screen_technical. Notes: KR/US/TW prices are adjusted for corporate actions but not dividends (indicators around dividend events may be slightly distorted); US history starts 2023-03-28 (volume from 2024-07-01) so long-window figures are shallower there. This is an approximation of a discretionary method, not a faithful reproduction. Market data, not investment advice. Errors: an empty result is not an error (count 0 = nothing passed today); 'database has not been built yet' -> ingest/indicators has not run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax rows, 1-50 (default 20)
orderNoSort direction (default desc)desc
marketNoMarket: 'kr' (default), 'us', 'tw', or 'all'. Japan has no redistributable price source, so it is not screenable.kr
rs_minNoMinimum RS percentile (default 80)
sort_byNoSort column (default rs_pctile)rs_pctile
min_priceNoMinimum close price (avoid low-priced stocks; e.g. 10 for US$, 5000 for KRW)
max_ext_pctNoMax % above the 10-day EMA before over-extended (default 15)
min_vol_avg20NoMinimum 20-day average volume (liquidity filter)
response_formatNo'markdown' for a table, 'json' for compact machine-readable outputmarkdown
require_ema_stackNoRequire 10-day EMA > 20-day EMA (default true)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYes
countYes
notesNo
orderNo
marketYes
signalsNo
sort_byNo
us_noteNo
criteriaNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that evaluation happens on the nightly indicators_latest snapshot, that prices are corporate-action-adjusted but not dividend-adjusted, that US history has known shallow periods, and that an empty result is not an error. It also explains the 'database has not been built yet' error case.

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 with labeled sections: approximation, conditions, args, returns, examples, usage, notes, and errors. It front-loads the core purpose and caveats. The Args section repeats some schema content, but every other section 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?

Given 10 parameters, zero required fields, a complex screening methodology, and an output schema, the description is remarkably complete. It defines the exact screening conditions, return fields, data caveats, use cases, alternatives, and error semantics. An agent has all the context needed to invoke and interpret this tool correctly.

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 schema already covers all 10 parameters with 100% description coverage, so the baseline is 3. The description adds meaning through rationale ('Kell trades leaders' for rs_min), concrete examples (e.g., min_vol_avg20: 500000, min_price 5000 KRW), and clarification of sort/format choices. It comfortably exceeds baseline but partially duplicates schema descriptions.

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: 'Screen KR, US and/or TW stocks for an Oliver Kell "Cycle of Price Action" long setup.' It also distinguishes itself from siblings in the 'Use when' paragraph, explicitly routing agents to screen_minervini for the 8-point trend template and screen_technical for arbitrary technicals.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly states when to use the tool — 'shortlisting momentum leaders riding short-term EMAs (Kell style, approximate)' — and when not to, warning not to treat a pass as a Kell 'buy'. It names concrete alternatives and gives worked examples for US and KR usage.

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 resource+action targets, and the overlapping screen_* tools are thoroughly cross-referenced with 'use screen_X instead' guidance. Minor ambiguity exists between get_disclosure_feed, get_dart_filings, and get_dart_major_events, which all surface KR filings from different angles but remain distinguishable.

Naming Consistency5/5

Every tool follows a consistent verb_noun snake_case pattern: get_* for retrievers, screen_* for screeners, search_* for lookups, plus action verbs like analyze_, backtest_, compare_, import_, and query_. Subfamilies (dart_*, edgar_*, fred_*, crypto_*) are consistently prefixed, making tool selection predictable.

Tool Count3/5

37 tools is heavy, and the four momentum screeners (canslim/kell/minervini/schwartz) plus three KR disclosure tools could arguably be collapsed into parameterized variants. However, the server's unusually broad scope—KR/US/TW/JP/EU equities, crypto, macro, portfolio, backtesting—means most tools earn their place, so the count is high but not chaotic.

Completeness4/5

The surface covers the core workflow well: search, prices, fundamentals, filings, insider trades, valuation, screeners, backtesting, and portfolio tracking for KR/US, plus crypto and macro. Notable gaps are the lack of single-company financial-statement tools for TW/JP/EU (only available through screen_companies) and no real-time stock quotes, but these are workable for the stated local-database research purpose.

Resources