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TheStrat for agents

buy_sell_list

Buy list and sell list: reversal signals in force across timeframes (technical signals screener on your own data). Buy: hammer, 2d-2u, 3-2u, 1-2u in force. Sell: shooter, 2u-2d, 3-2d, 1-2d in force. Continuations (2u-2u, 2d-2d) do not count. Per timeframe: symbols, count, % of basket, trigger, target and level of reclaim; plus which timeframes each symbol is on.

Input Schema

NameRequiredDescriptionDefault
nowNoCurrent time, ISO 8601. Decides if the last bar is still open. Default: the server clock.
as_ofNoOptional ISO time. Use only bars that start at or before this time (replay a past bar).
basket_by_timeframeYesBars per timeframe, then per symbol: {"M": {"AAPL": [...], ...}, "W": {...}}. Up to 4 timeframes; 60 symbols and 500 bars per symbol each.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It usefully discloses the output composition (symbols, count, percent of basket, trigger, target, reclaim level, and timeframes per symbol) and the signal inclusion criteria, but it does not explicitly state read-only behavior, performance limits, or data-handling constraints.

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 dense but appropriately front-loaded with the core purpose, followed by pattern criteria and output details. The pattern enumerations are necessary domain content rather than filler, though the semicolon-separated structure could be easier to scan.

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?

Given a complex nested basket input, no output schema, and no annotations, the description does well to explain the signal criteria and the returned fields per timeframe. Remaining parameter details are covered by the fully documented schema, so the definition is nearly complete for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already explains now, as_of, and basket_by_timeframe in detail. The description adds no parameter-specific syntax or defaults beyond implying that the screener operates on the user's basket data, so the baseline score of 3 is appropriate.

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 states a specific analytical operation: producing buy and sell lists of reversal signals in force across timeframes from the user's own bar data. It clearly defines buy patterns versus sell patterns, but it does not distinguish this tool from close siblings such as signals_in_force or find_signals.

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

Usage Guidelines3/5

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

The description implies usage by explaining which patterns count as buy or sell signals and that continuations do not count. However, it gives no explicit guidance on when to choose this tool over alternatives like signals_in_force or find_signals, and no exclusions are stated.

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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