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Glama

anon_post_physical_items_item_id_log

Destructive

Records stock quantity adjustments or status changes for a physical item, ensuring deltas are integer, results non-negative, and statuses valid while logging each update.

Instructions

记录物资数量变动。需 materials:manage 权限。数量类变动(adjust_on_hand/adjust_used/adjust_lost)的 delta 须为整数且结果不能为负;status_change 须带合法 status。每次成功记录一条日志(status_change 日志的 status 字段记录目标状态)。 POST /api/projects/{id}/physical/items/{itemId}/log 项目由当前 API 密钥自动确定,无需传 projectId。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, idempotentHint=false, so safety is covered. The description adds real behavioral context beyond that: it requires materials:manage, enforces validation rules (delta integer, result must not go negative), and states that each successful call appends exactly one log entry.

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 purpose, then permission, then per-type validation rules, then endpoint mechanics. Dense but each clause earns its place; the endpoint line is arguably redundant with the tool name but anchors the call.

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 still explains the return behavior (one log entry appended, status field records target status). Permission and project-scoping ('project auto-determined by API key, no projectId needed') are covered, leaving only minor detail on the note field.

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?

Top-level schema coverage is 0%, so the description carries the burden, and it does: it maps the type enum members to their delta/status requirements and clarifies that the status field stores the target state on status_change. Only minor gaps remain (e.g. what note does, delta semantics for status_change).

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 (记录/record) and resource (物资数量变动/material quantity change), and pins the exact endpoint POST /api/projects/{id}/physical/items/{itemId}/log. An agent can distinguish this write-log action from the sibling read tool anon_get_physical_items_item_id_logs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

It names a prerequisite (materials:manage permission) and the conditions selecting each log type, which is genuinely useful context. However it never says when to use this log endpoint versus alternatives like anon_patch_physical_items_item_id, so routing between write tools 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.

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