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Clarity Decision Matrix

Calculate decision matrix

calculate_decision_matrix
Read-onlyIdempotent

Use this when the user wants a weighted decision matrix, scored comparison, alternative ranking, or weight sensitivity analysis with explicit criteria, weights and scores. Accepts two to twenty options and one to eight criteria. Scores use a fixed zero-to-one-hundred scale; benefit means higher is better and cost means lower is better. Returns normalized weights, exact rankings and ties, pairwise break-even shares, up to four explicit weight scenarios and CSV. Does not research options, invent scores, infer preferences or predict outcomes.

Input Schema

NameRequiredDescriptionDefault
titleNoComparison title, e.g. Supplier shortlist.
optionsYesAlternatives with supplied ratings, e.g. [{"name":"A","scores":[80,40]},{"name":"B","scores":[60,20]}].
criteriaYesCriteria in the same order as each option score array, e.g. [{"name":"Quality","weight":60,"direction":"benefit"},{"name":"Expense","weight":40,"direction":"cost"}].
scenariosNoOptional explicit weight scenarios, e.g. [{"label":"Cost emphasis","weights":[20,80]}].

Output Schema

NameRequiredDescriptionDefault
tiedYes
notesYes
titleYes
rankingYes
winnersYes
criteriaYes
downloadsYes
scenariosYes
sensitivityYes
option_countYes
preview_onlyYes
winner_countYes
winners_preview_onlyYes
sensitivity_preview_onlyYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/non-destructive annotations, the description discloses the fixed 0-100 scoring scale, the benefit-vs-cost interpretation, enforced limits (2-20 options, 1-8 criteria, up to 4 scenarios), and that output includes normalized weights, exact rankings and ties, break-even shares and CSV. This is unusually rich behavioral context for a read-only calculation tool.

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?

Front-loaded with the trigger condition, then scales, then return contents, then exclusions. Dense but no filler sentence; every clause carries information an agent needs.

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?

Even though an output schema exists, the description summarizes return contents, and it covers scoring semantics, cardinality limits, and out-of-scope behaviors. Nothing needed to invoke it correctly is missing.

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?

With 100% schema description coverage the baseline is 3; the description reinforces the critical semantics an agent must get right—fixed 0-100 scale and benefit/cost direction—and states the option/criteria count bounds. Most of these are also in the schema, so it adds value but not substantial new parameter detail.

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 states a specific verb and resource (weighted decision matrix / scored comparison) and enumerates the output kinds it produces. An agent can tell exactly what the tool computes without opening the 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 gives an explicit trigger ('Use this when the user wants a weighted decision matrix, scored comparison, alternative ranking, or weight sensitivity analysis') and explicit exclusions ('Does not research options, invent scores, infer preferences or predict outcomes'). That is a complete when-to-use / when-not-to-use contract.

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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