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Glama

inspect_place

Retrieve historical and administrative context for any Chinese place and year, including ruling dynasty, region, and 2,400-year lore, with a shareable deep link.

Instructions

Query the historical and administrative context of a Chinese city, poem landmark, strategic pass, battlefield, or multi-stop route on the Jiangshan Historical Atlas (403 BCE – 2026 CE). Returns the reigning monarch/era, controlling regime (polity), macro-region (dao/lu/province), prefecture (jun/zhou/fu), modern province/city, 2,400-year city/pass lore, and a shareable deep-link URL.

Input Schema

NameRequiredDescriptionDefault
langNoResponse and deep-link UI language (default: "zh").
yearYesHistorical year (-403 to 2026, negative for BCE, no year 0) or comma-separated years for multi-year trajectories (e.g. "1079,1080,1094,1097").
placeYesCanonical ancient/modern place name in Chinese, English, or Pinyin (e.g. "长安", "蓝关", "浔阳", "Chang'an"), or comma-separated route stops (e.g. "剑外,巴峡,巫峡,襄阳,洛阳").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the behavioral burden and does well: it discloses the rich return fields (monarch/era, regime, macro-region, prefecture, modern location, lore, deep link) and the expansive temporal scope. It omits operational details like read-only status (implied by 'Query') and rate limits, but the return value transparency is strong.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two tightly written sentences: the first establishes the purpose and scope, the second enumerates the return fields. The return list is dense but every item earns its place by conveying what the agent will receive.

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 parameterized query tool with no output schema and no annotations, the description provides a good picture of inputs (entity types, temporal range) and outputs (specific returned fields plus deep-link URL). It leaves minor gaps like error behavior and explicit read-only confirmation, but nothing critical for correct invocation.

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 description coverage is 100%, so the schema already fully documents the year format, place format (including comma-separated routes), and language enum. The description adds no parameter-level meaning beyond confirming that multi-stop routes and historical entities are supported.

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

Purpose4/5

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

States a specific verb ('Query') and resource ('historical and administrative context of a Chinese city, poem landmark, strategic pass, battlefield, or multi-stop route') with a clear temporal scope. The entity type and atlas name distinguish it from inspect_person and search_atlas, though siblings are not explicitly named.

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?

Usage is implied by the query intent, but there is no explicit guidance on when to use this vs search_atlas or inspect_person, nor any when-not conditions. An agent must infer the appropriate 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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