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Glama
ilyautov

consilium-principis

close_decision_card

Record the actual outcome to finalize a decision card, validating numbers against original units and rejecting dates earlier than creation. Then trigger calibration.

Instructions

Закрыть Decision Card фактом исхода (МУТИРУЮЩИЙ, Rule 0): числа (occurred для event / actual в ТЕХ ЖЕ единицах для metric) идут в Card, глиф ✅/❌ остаётся человеку в markdown. Ищет карту по card_id (скан decisions/) или path. outcome={resolved_on, occurred|actual, endorsed?, note?}. Fail-closed: чужие единицы / дата раньше created → отказ. Потом зови prediction_calibration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNo
card_idNo
outcomeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.1

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden and discloses a lot: it is explicitly MUTATING (Rule 0), it is fail-closed (refuses foreign units and pre-created dates), and it explains the division of labor (numbers into the Card, glyph left to the human). Missing only things like persistence effect on existing card data or return behavior.

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?

Dense and front-loaded – the mutating nature and core behavior come first, then lookup mechanism, then outcome shape, then fail-closed rule and the follow-up call. Every clause carries information, though the packing is heavy.

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?

For a 3-param mutating tool with no annotations and no output schema, the description covers the mutation semantics, both lookup keys, the nested object, the failure policy, and the next step. It is close to complete, lacking only return-value expectations.

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?

Schema coverage is 0%, yet the description compensates: card_id scans decisions/ while path is the alternative, and it spells out the nested outcome shape {resolved_on, occurred|actual, endorsed?, note?} with unit semantics (occurred for event, actual in the same units for metric). This meaningfully exceeds the bare schema.

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?

States a specific verb ("Закрыть") plus resource ("Decision Card") and the exact scope of the operation – recording the outcome fact. It clearly distinguishes itself from save_decision_card (create) and prediction_calibration (a follow-up), so an agent can tell what it does 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 Guidelines4/5

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

Gives explicit sequencing ("Потом зови prediction_calibration") and preconditions (fail-closed on foreign units or a date before created). It implies the when-to-use context well but never explicitly contrasts with the sibling save_decision_card, so it stops short of full alternative routing.

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