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Cachly — AI Cognitive Brain

Cachly — AI Cognitive Brain

by cachly-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

brain_share_list

Lists previously shared Brain snapshots, returning share IDs, titles, lesson counts, visibility, and creation dates to help you track and manage your shared knowledge.

Instructions

List all Brain snapshots you have previously shared with brain_share. Shows share ID, title, lesson count, visibility, and creation date for each share. Checks the local provenance log and the cachly API. Example: brain_share_list(instance_id="...")

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "instance_id": "<instance_id>"
    },
    "name": "brain_share_list"
  }
}

Input Schema

NameRequiredDescriptionDefault
instance_idYesUUID of the Brain instance that created the shares.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.47

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions checking the local provenance log and the cachly API, which hints at multi-source behavior. However, it does not disclose side effects, authentication needs, rate limits, or whether it is safe to call repeatedly. The read-only nature is implied but not explicitly stated.

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 two sentences plus an example, all front-loaded. The first sentence states the purpose, the second lists the output fields, the third mentions data sources, and the example shows exact usage. 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 has one parameter, no output schema, and no annotations, the description effectively lists the returned fields and the data sources. It covers the essential information for an agent to use the tool. Missing details are minor (e.g., pagination, error handling, empty results).

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 description coverage is 100% (the single parameter 'instance_id' is described in the schema as 'UUID of the Brain instance that created the shares'). The description adds an example call but no additional semantics beyond the schema. Baseline 3 is appropriate.

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?

The description clearly states the verb 'list' and the resource 'Brain snapshots you have previously shared', and specifies the returned fields (share ID, title, lesson count, visibility, creation date). It distinguishes from sibling tools like brain_share (create) and brain_unshare (delete) by naming the specific action.

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 usage (to list shares) but does not explicitly state when to use this tool versus alternatives, nor does it provide prerequisites or exclusions. The example gives a usage pattern but no comparative guidance.

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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