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ilyautov

consilium-principis

save_decision_map

Saves a decision map as a decisions/-.json artifact with consent, returning its path and a ready journal line for the forecast.

Instructions

Сохранить карту решения артефактом decisions/<дата>-.json в корне доски (внутри — карта + МК-сводка с predicted). МУТИРУЮЩИЙ тул: зови ТОЛЬКО с явного согласия юзера (правило 0) — предложи ОДИН РАЗ после расчёта. Возвращает path + journal_line («Прогноз: 📐 …») — готовую строку прогноза для записи в журнал решений (§4.3). slug — латиница/цифры/дефисы.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
mapYes
seedNo
slugNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it flags the tool as MUTATING, states the consent requirement, describes the side effect (writes a JSON file), and describes the return value (path + journal_line). It omits overwrite behavior and permission details, keeping it short of a 5.

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?

Front-loaded with the core action and artifact path, then the mutation/consent warning, then the return value. Dense but every clause adds operational value; slightly heavy on parentheticals.

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?

It covers the side effect, consent gate, and return value well, but with no annotations, no output schema, and two fully undocumented parameters, an agent still lacks enough to call it reliably without guessing at n and seed.

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 0%, so the description must compensate for four parameters. It explains the slug format (latin/digits/hyphens) and what map contains, but n and seed are entirely undocumented, leaving half the parameters ambiguous.

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 names a specific verb (save) and resource (the decision map) and even specifies the exact artifact path decisions/<date>-<slug>.json plus its contents (map + MK-summary with predicted). This lets an agent distinguish it from save_decision_card/validate_decision_map 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 Guidelines4/5

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

It gives an explicit precondition and sequencing rule: call ONLY with the user's explicit consent and propose it ONCE after calculation. That is strong when-to-use guidance, though it never names a sibling alternative to compare against.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.