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space0

by space.0

Preview a card-post composition

compose_card_preview
Read-only

Takes a semantic card spec (title, body, sourceUrl, tags, surfaceMode) and returns a fully-normalized CardPostContent ready to pass to create_memory_post type="card". Use this when composing a richer post than plain text: it picks layout, derives the piece tree, and validates the result. On failure returns {ok:false,reason}. No side effects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNo
tagsNo
titleNo
mediaUrlNo
sourceUrlNo
sourceLabelNo
surfaceModeNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Discloses 'No side effects', aligning with readOnlyHint=true. Adds failure return format ({ok:false,reason}) and mentions validation. Annotations already cover read-only, but description provides context on behavior beyond that.

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 sentences: first describes input/output, second explains when to use and behavior. No redundant information, front-loaded with key facts.

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?

Covers input spec, output target (create_memory_post), failure case, and side-effect-free nature. No output schema exists, but the description gives enough for a preview tool. Missing details on normalization specifics, but adequate for the complexity.

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?

With 0% schema description coverage, the description must compensate. It lists some parameters (title, body, sourceUrl, tags, surfaceMode) but omits mediaUrl and sourceLabel, and does not explain their meaning or constraints. Partial compensation is insufficient for 7 parameters.

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?

Clearly states it takes a semantic card spec (title, body, sourceUrl, tags, surfaceMode) and returns a normalized CardPostContent for use with create_memory_post. Distinguishes itself by being a preview step for richer posts, not plain text.

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?

Explicitly says 'Use this when composing a richer post than plain text' and describes the normalization, layout selection, and validation. Does not state when not to use, but the purpose is clear enough to infer alternatives (e.g., plain text post).

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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TDQS

A3.7/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count2/5

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.

Completeness4/5

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.

Resources