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simoncoombes

tradefloor

by simoncoombes
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Python
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Trace a move to its random draws

explain
Read-onlyIdempotent

Trace one ticker's daily price move to the random draws behind it, showing a replayable factor tree with measured numbers from rerunning that day.

Instructions

Trace one name's price move on one day down to the random draws that caused it, as a tree: the day's log move at the top, then each factor, then the draw addresses beneath them. Every node can be replayed, and every number is measured by running the day again. Use explain_price_move to see which factors moved prices across the roster; use this for one name when you need to know which draws moved those factors. depth sets how much of the tree the render text shows. Builds and runs its own market for up to 60 days, under preset if one is named; read-only and deterministic.

Input Schema

NameRequiredDescriptionDefault
dayNoThe trading day to explain, 1 to 60.
seedNoSimulation seed, an integer from 0 to 2**64 - 1. The same seed and arguments give the same result.
depthNoHow many levels of the tree the `render` text shows, 0 to 4. The `tree` field is always whole.
presetNoA shipped model preset to run, by name: pt-v1, pt-v2, pt-v3, pt-v4, pt-v5, pt-v6, pt-v7, pt-v8, pt-v9, pt-v10, pt-v11, pt-v12, pt-v13, pt-v14, pt-v15, pt-v16, pt-v18, pt-v19, pt-v20, pt-v21. Omit for the shipped default, pt-v21, the only preset the realism envelope certifies; a result under any other carries a caveat saying it is outside the certification, with that preset's own measured record. describe_simulator lists every preset's record.
tickerNoOne ticker from the roster. Omit to take the largest moves (explain_price_move) or the first name (explain).
universeNoA roster document, usually the `universe` field of a build_universe result. Either {"size": n, "seed": s, "sectors": [...]} or {"instruments": [...]}. When given it replaces universe_size, universe_seed and universe_sectors.
universe_seedNoSeed that generates the roster, separate from the simulation seed. Ignored when `universe` is given.
universe_sizeNoNames in a generated roster, 2 to 120. Ignored when `universe` is given.
universe_sectorsNoLowercase sector ids to concentrate a generated roster on, for example ["technology", "energy"]. The ids: technology, financial_services, healthcare, energy, consumer_discretionary, consumer_staples, industrials, materials, real_estate, utilities, telecommunications, transportation. A concentrated roster is a named envelope gap, and the result says so.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.10.1
    • addedInput schema / properties / preset
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "A shipped model preset to run, by name: pt-v1, pt-v2, pt-v3, pt-v4, pt-v5, pt-v6, pt-v7, pt-v8, pt-v9, pt-v10, pt-v11, pt-v12, pt-v13, pt-v14, pt-v15, pt-v16, pt-v18, pt-v19, pt-v20, pt-v21. Omit for the shipped default, pt-v21, the only preset the realism envelope certifies; a result under any other carries a caveat saying it is outside the certification, with that preset's own measured record. describe_simulator lists every preset's record.",
+  "title": "Preset"
+}
  2. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint/idempotentHint/destructiveHint=false, so the safety profile is covered. The description adds genuinely new behavior: it builds and runs its own market for up to 60 days, every number is measured by re-running the day, and non-default presets return a caveat with that preset's own measured record. It doesn't describe cost or runtime, hence not a 5.

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?

Front-loads purpose and the tree shape, then alternatives, then parameter behavior, then operational constraints. Sentences are dense and slightly overpacked (preset caveats, build window, determinism in one clause), but every sentence carries information and nothing is redundant.

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?

An output schema exists, so return values need not be explained, and the description still covers the pieces an agent needs: determinism, read-only nature, the 60-day build, preset certification caveats, and depth's effect on rendered output. Nothing material is missing for a 9-param, zero-required tool.

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 coverage is 100%, so baseline is 3, but the description adds real meaning: `depth` governs only the `render` text while `tree` is always whole, `preset` determines which market gets built and whether a caveat appears, and `ticker` omission defaults to first name here vs largest moves in the sibling. That is value beyond the schema text.

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 (trace), resource (one name's price move on one day), and output shape (a tree: log move, factors, draw addresses). It explicitly distinguishes itself from explain_price_move, so an agent can route without opening either schema.

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?

Gives an explicit when-to-use split: explain_price_move for which factors moved prices across the roster, this tool for one name when you need to know which draws moved those factors. It also points at describe_simulator for preset records, covering the adjacent decision.

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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