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tresor4k

macalc

calculate_quadratic_equation

Solve quadratic equation ax²+bx+c=0 with discriminant analysis. Returns real or complex roots, discriminant, and vertex coordinates. Ideal for math homework and physics problems.

Instructions

Solve quadratic equation ax²+bx+c=0 with discriminant analysis. Use for math homework or physics problems. Inputs: coefficients a, b, c. Returns roots (real or complex), discriminant, and vertex. See list_bundles for related 'math' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aYesCoefficient a
bYesCoefficient b
cYesCoefficient c

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.
Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It explains that the tool returns real or complex roots, discriminant, and vertex, which is transparent. However, it does not mention edge cases like a=0 or precision.

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?

The description is three sentences, front-loads the purpose, and includes usage context and a cross-reference. Every sentence adds value without redundancy.

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 the tool's simplicity, the description covers purpose, usage, inputs, and expected outputs. An output schema exists, and the description sufficiently complements it.

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 coverage is 100%, with each parameter already described. The description adds 'Inputs: coefficients a, b, c' but does not provide additional meaning beyond the schema. Baseline score of 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 description clearly states the tool solves quadratic equations with discriminant analysis, specifies inputs, and explains outputs. It is specific and distinguishes from many sibling math calculators by name and purpose.

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

Usage Guidelines4/5

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

The description provides context for use ('math homework or physics problems') and mentions related calculators, but does not explicitly state when not to use this tool or contrast with alternatives.

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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