areas
areasList the knowledge areas in this Lady Whiskerdown.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
kit-memory-demo
Schema Changelog
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
- First observed
TDQS
A3.6/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide only title, so description must carry behavioral weight. It implies a read-only list operation but does not explicitly confirm no side effects or state what 'Lady Whiskerdown' means. Adequate for a simple tool but lacks explicit safety guarantees.
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?
Single sentence of 9 words with zero fluff. Every word is necessary for the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, the description fails to hint at response format or what a 'knowledge area' constitutes. A simple tool still needs to inform the agent about what to expect in return.
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?
No parameters exist; baseline score is 4 as per rubric. Description adds context about 'knowledge areas' and 'Lady Whiskerdown' which marginally enhances understanding beyond the empty schema.
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?
Description uses specific verb 'List' and resource 'knowledge areas', clearly distinguishing from sibling tools which are action verbs like capture, commit, focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; no mention of prerequisites or context where this listing is appropriate.
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 distinct purposes like listing areas, capturing drafts, committing memories, and searching. However, the 'note' and 'handoff' tools overlap significantly because 'note' can be used with kind=handoff for the same scenarios that 'handoff' is designed for, potentially confusing an agent on which to use.
Naming Consistency4/5
Tool names are all single-word, lowercase, and descriptive. Most are verbs (capture, commit, focus, etc.), but 'areas' and 'presence' are nouns, introducing a minor inconsistency. Overall, the pattern is simple and readable.
Tool Count5/5
With 10 tools covering listing, capturing, committing, searching, retrieving, and setting context, the count is well-scoped for a memory/knowledge management server. Each tool serves a clear purpose and fits within the domain.
Completeness2/5
The tool surface lacks update and delete operations for memories, which are essential for a complete lifecycle. There is no way to modify or remove committed memories, and no tool to list all memories (only semantic search). This creates significant gaps that will likely cause agent failures.