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tradefloor

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Python
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Explain a price move by factor

explain_price_move
Read-onlyIdempotent

Break down a simulated day's price move into 12 factor contributions to the mispricing gap. Identify which factors drove the largest moves, or trace a specific ticker's move back to its random draws.

Instructions

Break one day's move for each name into the 12 factor contributions that sum to the day's change in the mispricing, the log gap between the model price and fair value. Use it to ask which factors moved prices; use explain to trace one name's move down to the random draws behind it. They are the simulator's own bookkeeping, and they are not the whole price move. On the default preset most of the day's news and noise moves fair value, fair_value_shift takes that part out of the mispricing, and the fair-value move itself is not split up. Without a ticker it returns the top_n largest moves. Builds and runs its own market for up to 60 days, under preset if one is named; read-only.

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.
top_nNoHow many instruments to return, largest moves first, when no ticker is given. 1 or more.
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

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive (and the description redundantly repeats 'read-only'), so the bar is lower. The description nevertheless adds real behavioral context: these contributions are the simulator's own bookkeeping and are NOT the whole price move, `fair_value_shift` removes the news/noise part on the default preset, fair-value moves aren't split up, and it builds/runs its own market for up to 60 days. That is substantial disclosure beyond the annotations.

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?

Purpose is front-loaded and sentences carry real information, but the prose is dense and slightly meandering ('They are the simulator's own bookkeeping, and they are not the whole price move'), and 'read-only' duplicates the annotation. Mostly earned, minor padding.

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 covers the concept (mispricing), the exclusion caveat, the top_n fallback, the preset caveat, and the 60-day build limit. For a 9-parameter analytical tool nothing an agent needs to call it correctly is missing.

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 documents day, seed, top_n, preset, ticker, and the universe fields in detail, including the preset certification caveat. The description adds only the cross-parameter behavior 'without a ticker it returns the top_n largest moves', which the schema's ticker description already states. Baseline 3 is appropriate.

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 first sentence gives a specific verb (break) plus resource (one day's move per name into 12 factor contributions) and even defines the key term 'mispricing' as the log gap between model price and fair value. It explicitly contrasts the scope with the sibling `explain` (whole-cross-section vs. one name down to random draws), so an agent can select it without opening any 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?

It states the use case directly ('Use it to ask which factors moved prices') and names the alternative tool `explain` with the distinguishing condition (trace one name's move down to the random draws). When-to-use and the alternative are both explicit.

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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