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Cachly — AI Cognitive Brain

Cachly — AI Cognitive Brain

by cachly-dev
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

brain_metrics

Report three decisive cognitive metrics: onboarding friction, recall lift over BM25, and team-knowledge reuse rate. Use to verify that the AI Brain delivers measurable value from shared lessons.

Instructions

Report the three decisive Brain metrics: (1) time-to-first-recall (onboarding friction), (2) recall-lift vs. raw BM25 (the moat proof, from Cachly-Bench), and (3) team-knowledge-reuse — what % of proven recalls used a teammate's lesson. Use to track whether the Brain is delivering its core value. Pass author="handle" to smart_recall so cross-author reuse can be measured.

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_metrics"
  }
}

Input Schema

NameRequiredDescriptionDefault
instance_idYesUUID of the cache instance

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.10.47

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, and the description does not disclose whether the tool is read-only, has side effects, requires permissions, or triggers calls to smart_recall. The hint about passing author to smart_recall is ambiguous about this tool's own behavior.

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 three sentences long, front-loaded with the main metrics, and contains no redundant information. Every sentence earns its place.

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?

Given the tool has one parameter and no output schema, the description explains the function and purpose adequately. However, it does not describe the return format or structure, and the smart_recall hint adds confusion about cross-tool integration.

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?

The schema already describes the parameter instance_id as 'UUID of the cache instance' (100% coverage). The description adds no additional semantic detail about this parameter beyond the schema, which is the baseline expectation.

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 reports three specific Brain metrics with brief explanations, making its purpose precise. However, it does not explicitly distinguish this tool from sibling tools like brain_discover or brain_conflicts, which could overlap in concept.

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?

The description advises when to use it ('Use to track whether the Brain is delivering its core value') and provides a usage hint about passing an author handle to smart_recall. However, it lacks explicit exclusions or alternatives to other tools.

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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