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kernl

kernl

by fastslack
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

kernel_chat_analyze

Analyze the concept graph to surface top concepts by importance and reveal community structure, helping you understand key themes and relationships in your memory data.

Instructions

Run analytics on the concept graph. Shows top concepts by importance and community structure.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "kernel_chat_analyze"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.1

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It implies a read-only inspection via "Shows" and hints at the return content, but it never states scope (which graph or chat), whether the analysis is expensive or cached, how many concepts are returned, or whether results are ranked/filtered.

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?

Two short sentences with no filler, and the core action is front-loaded. The text is efficiently written, though its brevity leaves the gaps noted in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no input parameters and no output schema, the description is the only source of return-value information, and it gives only a high-level sketch (top concepts, communities). For a zero-arg analytics tool, the missing scope, result size, and ranking details leave it adequate but incomplete.

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?

The tool takes zero parameters, so there is no parameter semantics to document and the baseline of 4 applies. Nothing in the description confuses or misrepresents the argument-free call signature.

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

Purpose3/5

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

The description pairs the verb "Run analytics" with the resource "concept graph" and names two outputs (top concepts by importance, community structure). However, "analytics" is generic and it offers no differentiation from the similarly named sibling kernel_graph_analyze, so an agent cannot tell which one to pick from the text alone.

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?

There is no when-to-use guidance, no preconditions, and no named alternative such as kernel_graph_analyze or kernel_chat_concepts. The agent must infer that this is a summary/overview tool by reading 'top concepts' and 'community structure'.

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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