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Cachly — AI Cognitive Brain

Cachly — AI Cognitive Brain

by cachly-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

brain_discover

Search and browse publicly shared Brain snapshots to find ready-made knowledge bases on specific topics. Returns ranked results with lesson counts and import commands.

Instructions

Search and browse publicly shared Brain snapshots in the cachly marketplace. Find ready-made knowledge bases on specific topics (TypeScript, Docker, auth, CI/CD, etc.) created and shared by the community. Returns a ranked list with lesson counts, topics, and import commands. Example: brain_discover(query="kubernetes deployment") · brain_discover(topic="auth")

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": "brain_discover"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMax number of results to return (default 10, max 50).
queryNoFull-text search query across Brain titles and descriptions.
topicNoFilter by topic prefix (e.g. "auth", "docker", "nextjs").

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.47

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It describes the tool as searching and browsing, implying a read-only operation. It mentions the return content (ranked list, lesson counts, etc.) but does not explicitly state non-destructive behavior, auth requirements, or rate limits. Adequate but not fully transparent.

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?

The description is short (two sentences plus an example) and front-loaded with the main purpose. Every sentence adds value without redundancy. No wasted words.

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?

Given the tool's simplicity (3 optional parameters, no output schema), the description covers the core functionality, return types (lesson counts, topics, import commands), and provides examples. It is complete enough for an agent to use correctly, though it could be slightly more explicit about result structure.

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 coverage is 100% with descriptions for all three parameters. The description adds examples of usage (query and topic) and notes the output types, but does not significantly extend the meaning beyond what the schema provides. Hence baseline 3.

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?

The description clearly states the tool searches and browses publicly shared Brain snapshots, with specific verbs and resource. It gives examples of usage. However, it does not explicitly distinguish from sibling tools like brain_search or brain_marketplace, which may have overlapping functionality.

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?

The description implies when to use (to find ready-made knowledge bases by topic or query) but does not provide explicit guidance on when not to use or mention alternatives. The examples help, but no exclusions or comparisons are given.

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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