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POST
/
teams
/
fault-lines
Analyze team fault lines
curl --request POST \
  --url https://api.mnemom.ai/v1/teams/fault-lines \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "team_id": "<string>",
  "agent_ids": [
    "<string>"
  ],
  "dimensions": [
    "capabilities"
  ]
}
'
{
  "team_id": "<string>",
  "analysis_id": "<string>",
  "fleet_score": 50,
  "fault_lines": [
    {
      "id": "<string>",
      "value": "<string>",
      "classification": "capability_gap",
      "severity": "low",
      "agents_declaring": [
        "<string>"
      ],
      "agents_missing": [
        "<string>"
      ],
      "impact_score": 0.5,
      "resolution_hint": "<string>"
    }
  ],
  "summary": "<string>"
}

Authorizations

Authorization
string
header
required

Supabase JWT token in Authorization: Bearer header

Body

application/json
team_id
string
required

Team identifier to analyze

agent_ids
string[]

Optional subset of agent IDs to analyze. If omitted, all team members are analyzed.

dimensions
enum<string>[]

Dimensions to analyze for fault lines

Available options:
capabilities,
values,
constraints,
tools,
policies

Response

Fault line analysis result

Complete fault line analysis result for a team.

team_id
string

Team that was analyzed

analysis_id
string

Unique identifier for this analysis run

fleet_score
number

Overall fleet alignment score (0-100)

Required range: 0 <= x <= 100
fault_lines
object[]

Identified fault lines sorted by severity

summary
string

Human-readable summary of the analysis findings