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tresor4k

macalc

calculate_card_draw_probability

Calculate hypergeometric probability of drawing a specified number of target cards from a deck. Enter deck size, target cards in deck, draw count, and desired hits to get odds.

Instructions

Calculate hypergeometric probability of drawing specific cards from a deck. Returns: {odds_one_in}. See list_bundles for related 'jeux-probabilites' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deck_sizeNoTotal number of cards in the deck (default 52)
cards_in_deck_matchingYesNumber of target cards in the deck
draw_countYesNumber of cards drawn
target_cardsYesNumber of target cards wanted in the draw

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior3/5

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

Without annotations, the description discloses the return format but lacks detail on edge case handling (e.g., invalid input combinations). Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the main action, and includes a useful cross-reference. No superfluous content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With full schema and output schema present, the description is mostly adequate but omits behavioral notes on input validation or distribution assumptions, which would aid completeness.

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 baseline is 3. The description adds little beyond 'hypergeometric probability', not elaborating on parameter constraints.

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 clearly states the tool calculates hypergeometric probability for card draws, specifying the return format and referencing related calculators. It distinguishes from sibling tools like calculate_dice_probability.

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

Usage Guidelines2/5

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

The description only mentions related calculators via list_bundles but does not provide explicit guidance on when to use this tool versus alternatives, nor when not to use it.

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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