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Get one decision with its options

klengnest_get_decision
Read-onlyIdempotent

What to look for, how many to buy, the safety notes, and the options ranked on their own merits (no personal answers). For clothing, size_plan gives how many per size; a null count means no source gives one. A decision with no products says what to look for instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
decision_keyYesFrom klengnest_list_categories, e.g. "11-clothing/bodysuits"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: rankings exclude personal answers, a null size count means no source supplies one, and a decision with no products falls back to 'what to look for'. Since no output schema exists, this return-shape detail is doing needed work.

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?

Two dense sentences with no filler; the payload contents come first and the edge-case semantics follow. Slightly scattershot — the size_plan clause interrupts the flow of the return-shape list — but nothing is wasteful.

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

Completeness4/5

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

With no output schema, the description reasonably covers what comes back (look-for guidance, quantities, safety notes, ranked options) plus two important special cases. It omits any relationship to the sibling lookup tools, but for a single-key read it is nearly complete.

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?

Only one parameter and schema description coverage is 100% — the schema already states decision_key is sourced from klengnest_list_categories with an example value. The description adds nothing about the key's format or origin, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description enumerates what the decision object contains (what to look for, how many to buy, safety notes, ranked options), which is specific but never states the action or resource in verb+noun form — the verb 'Get' lives only in the title. It also never contrasts itself with klengnest_get_product or klengnest_search_products, so the boundary between a 'decision' and a 'product' is left to inference.

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?

No when-to-use guidance and no mention of any sibling alternative, even though klengnest_get_product and klengnest_search_products are obvious candidates for confusion. It only covers data edge cases (null count, decision with no products), not invocation context.

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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