get_cellPoint query for ONE grid cell. Returns {solid, material_id, source}. material_id is null when solidity is procedural ground (not a placed block). Use for a surgical adjacency check; for a box use inspect_region.
| Name | Required | Description | Default |
|---|---|---|---|
| gx | Yes | ||
| gy | Yes | ||
| gz | Yes | ||
| space | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / additionalPropertiesAdded value: +falseInput schema / properties / gx / maximumRemoved value: -9007199254740991Input schema / properties / gx / minimumRemoved value: --9007199254740991Input schema / properties / gy / maximumRemoved value: -9007199254740991Input schema / properties / gy / minimumRemoved value: --9007199254740991Input schema / properties / gz / maximumRemoved value: -9007199254740991Input schema / properties / gz / minimumRemoved value: --9007199254740991Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true. The description adds useful behavioral details: return shape and the edge case of null material_id for procedural ground. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, each adding value. No redundancy or unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers return structure and a key edge case, but lacks parameter explanations and does not specify coordinate system or space context. For a simple tool with 4 required params, this is adequate but with gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description does not explain the meaning of parameters (gx, gy, gz, space). It only implies coordinates via 'Point query', which is insufficient for correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Point query for ONE grid cell' with specific verb and resource, and distinguishes from sibling 'inspect_region' by stating 'for a box use inspect_region'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use for a surgical adjacency check; for a box use inspect_region', providing clear when-to-use and when-not-to-use with a specific alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes, with detailed descriptions differentiating them. However, the high count (60) introduces some overlap among memory-related tools (e.g., recall_nearby_memories, search_memories, recent_memory) and environment inspection tools (look_around, look_at, survey_site), causing minor ambiguity.
The majority of tools follow a consistent verb_noun pattern (e.g., enter_space, create_commitment, recall_nearby_memories). A few names break pattern, like cognitive_boot (adjective_noun) or who_is_here (phrase), but overall the naming is predictable and readable.
With 60 tools, the server exceeds the high end of the typical well-scoped range (3-15). While the domain is complex, many tools could be consolidated (e.g., multiple memory retrieval and building tools), making the surface feel bloated rather than lean and focused.
The tool set covers the core functionalities of the 3D world—spatial navigation, building, memory, commitments, skills, and social interaction—with few obvious gaps (e.g., no direct region deletion or agent interaction beyond chat). The breadth is appropriate for the domain, though some redundancy suggests minor over-engineering.