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Glama

rx_whats_new

Read-only

Retrieves new Directum RX activity since the last check: incoming assignments, notifications, due today, overdue items, and completed tasks. Use at start of day to catch up.

Instructions

Что нового в Directum RX с прошлого раза: пришедшие задания и уведомления, что со сроком до конца дня (включая просроченное), какие мои задачи завершились. Используйте для вопросов «что нового», «что пришло, пока меня не было», в начале рабочего дня. По умолчанию показывает всё с прошлого вызова rx_whats_new и сдвигает отметку на текущий момент; since задаёт начало явно, peek=true не сдвигает отметку. Подробности по строке: rx_get_assignment, rx_get_task. Только чтение RX.

Input Schema

NameRequiredDescriptionDefault
peekNotrue = только посмотреть, не сдвигая отметку прошлого просмотра
limitNoсколько строк в каждом разделе, по умолчанию 20, максимум 100
sinceNoс какого момента: 24h, 3d, 1w, today, дата 2026-10-15 или 15.10.2026; по умолчанию с прошлого вызова rx_whats_new, а при первом вызове за сутки

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.1

TDQS

A4.5/5.0
Behavior4/5

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

Goes beyond the readOnlyHint annotation by disclosing the cursor/mark semantics: the default advances the mark to now, since sets it explicitly, and peek=true suppresses the advance. This state-mutating side effect is exactly the kind of behavior an agent needs and it does not contradict idempotentHint=false. Minor gap: no note on what happens if the mark is stale.

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-loads the returned content, then usage, then mechanics, in a compact paragraph with no filler. Slightly dense but every clause contributes; could be split for scannability.

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 carries return-value burden and does describe the three sections returned, plus the limit semantics (rows per section). Sufficient for correct invocation; a brief note on the response shape or ordering would round it out.

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 100% so the baseline is 3, but the description adds relational meaning the schema states only per-parameter: how since, peek, and the default cursor interact to determine the reporting window. That cross-parameter semantics is genuine added value.

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 resource and enumerates exactly what it surfaces: incoming assignments/notifications, items due by end of day including overdue, and the user's completed tasks. This is clearly distinguishable from sibling list tools like rx_my_assignments or rx_list_tasks.

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?

Gives explicit triggering contexts ('что нового', 'что пришло, пока меня не было', start of the workday) and routes the agent to the correct follow-up tools (rx_get_assignment, rx_get_task) for row details. Nothing is left to inference.

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