Cachly — AI Cognitive Brain

brain_conflicts

List unresolved belief conflicts where a confirmed fix contradicts a later failure, plus active agents writing to the brain. Use this arbitration inbox to detect multi-agent overwrites and resolve contradictions.

Instructions

READ-ONLY — list every unresolved belief_conflict (a previously confirmed fix now contradicted by a failure) plus the agents currently writing to this Brain (last 1h). This is the arbitration inbox for multi-agent teams: when several AI sessions share one Brain, contradictory writes surface here instead of silently overwriting each other. Resolve any listed conflict with brain_resolve_conflict.

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_conflicts"
  }
}

Input Schema

Name	Required	Description	Default
`instance_id`	Yes	Brain instance ID

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.10.47Aug 18, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description fully discloses that the operation is READ-ONLY and specifies the scope (last 1 hour). It explains the behavioral nuance of surfacing conflicts instead of silent overwrites, providing valuable context beyond a simple 'list'.

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, front-loaded with 'READ-ONLY', and every sentence adds value. No redundant or unnecessary information.

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

Completeness5/5

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

Given the single parameter, no output schema, and explanatory context about conflicts and agent writes, the description is complete. An agent can understand what the tool returns and why it exists.

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 instance_id described as 'Brain instance ID'. The description does not add extra semantic detail about the parameter, so 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 tool lists unresolved belief conflicts and writing agents, framing it as an arbitration inbox. It distinguishes itself from the sibling tool brain_resolve_conflict by noting that conflicts can be resolved with that tool.

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 explains when to use the tool (when multi-agent teams share a Brain and contradictory writes occur) and directs users to brain_resolve_conflict after listing. It does not explicitly state when not to use it, but the context is sufficiently clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server