> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mnemom.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Team Trust Rating

> The Team Trust Rating — a composite trust metric for teams of AI agents. Built from coherence history, member quality, operational record, structural stability, and assessment density.

## Overview

The Team Trust Rating extends the [Mnemom Trust Rating](/concepts/reputation-scores) to **teams of AI agents**. While individual Trust Ratings measure a single agent's trustworthiness, the Team Trust Rating evaluates whether a group of agents operates reliably *together* — accounting for coherence dynamics, roster stability, and collective operational history.

Teams are first-class meta-agents in Mnemom. They have persistent identity, their own alignment cards, accumulated reputation, and cryptographic proofs — independent of any individual member.

Key properties:

* **Persistent identity** — A team's reputation persists across roster changes. Adding or removing a member adjusts the score incrementally, not from scratch.
* **Compositional but independent** — Team scores are informed by member scores (via the Member Quality component) but are not a simple average. Teams with identical members can have different scores based on their operational history.
* **Same grade scale** — Teams use the same AAA–NR grade scale and 0–1000 score range as individuals, enabling direct comparison.
* **Lower eligibility bar** — Teams need 10 team risk assessments for eligibility (vs. 50 integrity checkpoints for individuals), reflecting their inherently collaborative, less frequent evaluation cycles.

<Note>
  The Team Trust Rating requires a minimum of **10 team risk assessments** before a public score is published. This threshold prevents gaming through selective assessment submission while remaining achievable for active teams.
</Note>

***

## Score range and grades

Team scores use the same grade scale as individual agents:

| Grade   | Score Range | Tier        | Meaning                                                                  |
| ------- | ----------- | ----------- | ------------------------------------------------------------------------ |
| **AAA** | 900 -- 1000 | Exemplary   | Consistently demonstrates exceptional team alignment and coordination.   |
| **AA**  | 800 -- 899  | Established | Strong team track record with minimal operational issues.                |
| **A**   | 700 -- 799  | Reliable    | Solid team performance with occasional minor concerns.                   |
| **BBB** | 600 -- 699  | Developing  | Building a track record. Some team-level issues but trending positively. |
| **BB**  | 500 -- 599  | Emerging    | Limited or mixed team history. More assessments needed.                  |
| **B**   | 400 -- 499  | Concerning  | Elevated team risk or significant roster instability.                    |
| **CCC** | 200 -- 399  | Critical    | Serious team-level concerns. Human oversight recommended.                |
| **NR**  | --          | Not Rated   | Fewer than 10 team risk assessments. Score is being built.               |

***

## Score components

The Team Trust Rating is a weighted sum of five normalized components, each scored 0–1000:

```
TeamTrustScore = 0.35 × coherence_history
               + 0.25 × member_quality
               + 0.20 × operational_record
               + 0.10 × structural_stability
               + 0.10 × assessment_density
```

The score is clamped to the 0–1000 range.

### Coherence history (35%)

The dominant component. Tracks historical trends in the team's Coherence Quality (CQ) pillar from [team risk assessments](/concepts/risk-assessment#team-risk).

CQ measures pairwise compatibility across four dimensions — value overlap, priority alignment, behavioral correlation, and boundary compatibility. The coherence history component smooths CQ over time, rewarding teams that maintain or improve their internal alignment.

* **Data source:** CQ pillar values from team risk assessments
* **Update frequency:** Every team risk assessment
* **Improvement lever:** Align member values, resolve pairwise conflicts, maintain consistent team composition

### Member quality (25%)

Tail-risk-weighted aggregate of individual member Trust Ratings, using the same CoVaR-inspired (Conditional Value at Risk) weighting from the [team risk engine](/concepts/risk-assessment#team-risk). Members with lower individual scores receive exponentially more weight — one poorly-rated member drags the team score down more than one highly-rated member lifts it up.

* **Data source:** Individual [Mnemom Trust Ratings](/concepts/reputation-scores) (read-only — team scoring never modifies individual scores)
* **Update frequency:** When individual member scores change
* **Improvement lever:** Ensure all members maintain strong individual Trust Ratings; address the weakest member first

<Info>
  Member Quality is a read-only consumer of individual Trust Ratings. A team's Member Quality component cannot affect or modify any individual agent's score.
</Info>

### Operational record (20%)

Measures the proportion of team risk assessments that resulted in low or medium risk levels. Teams that consistently pass risk assessments with favorable outcomes build a strong operational record.

```
operational_record = (low_and_medium_assessments / total_assessments) × 1000
```

* **Data source:** Historical team risk assessment results
* **Update frequency:** Every team risk assessment
* **Improvement lever:** Address root causes of high-risk assessments; improve team coherence before requesting new assessments

### Structural stability (10%)

Tracks two factors: Structural Risk (SR) pillar trends from risk assessments and roster churn rate. Teams with stable membership and low contagion risk score higher.

A roster churn penalty is applied when members are frequently added or removed. The penalty decays over time — a team that stabilizes its roster recovers within weeks.

* **Data source:** SR pillar values + roster change frequency
* **Update frequency:** Every risk assessment and roster change
* **Improvement lever:** Minimize unnecessary roster changes; maintain consistent team composition

### Assessment density (10%)

A logarithmic count of team risk assessments weighted by recency. More recent assessments count more. This component rewards teams that are actively assessed rather than scoring high on a small, stale data set.

```
assessment_density = log(1 + recent_weighted_count) × recency_multiplier × 1000
```

* **Data source:** Team risk assessment timestamps
* **Update frequency:** Every team risk assessment
* **Improvement lever:** Request regular risk assessments for the team, especially during active operational periods

***

## Confidence levels

The number of team risk assessments determines the confidence level:

| Confidence       | Assessment Count | Display                        |
| ---------------- | ---------------- | ------------------------------ |
| **Insufficient** | \< 10            | Score not published (NR grade) |
| **Low**          | 10 -- 29         | "Low Confidence" indicator     |
| **Medium**       | 30 -- 99         | "Medium Confidence" indicator  |
| **High**         | ≥ 100            | "High Confidence" indicator    |

<Warning>
  The 10-assessment minimum is a hard gate for score publication. Teams below this threshold display an "NR" (Not Rated) badge with a progress indicator showing assessments remaining until eligibility.
</Warning>

***

## Score computation

### Frequency

* **6-hour cron:** Team scores are recomputed every 6 hours from the latest data
* **On-demand triggers:** Score recomputation is also triggered by roster changes and new risk assessments
* **Weekly snapshots:** A frozen snapshot is saved each Monday at 00:00 UTC for historical trend tracking

### Anti-gaming measures

1. **Minimum assessment count** — 10 team risk assessments required before score publication
2. **Tail-risk weighting** — Member Quality uses CoVaR weighting, preventing a team from hiding a weak member behind strong ones
3. **Roster churn penalty** — Rapidly cycling members to game the composition is penalized via the Structural Stability component
4. **Independent assessment** — All team risk assessments are computed by the Mnemom risk engine, not self-reported

### Trend tracking

Every `TeamReputationScore` includes a `trend_30d` field — a signed delta comparing the current score to 30 days ago:

* **Positive trend (+):** Score is improving
* **Negative trend (-):** Score is declining
* **Flat trend (0):** Score is stable

***

## Team alignment cards

Teams have their own [alignment cards](/concepts/alignment-cards) that declare the team's collective values, autonomy boundaries, and coordination mode.

### Auto-derivation

The most common approach is auto-deriving the team card from member cards:

```
POST /v1/teams/{team_id}/card/derive
```

The derivation algorithm:

* **Values:** Union of all member values, ordered by frequency (most common first)
* **Bounded actions:** Union of all member bounded actions
* **Forbidden actions:** Union of all member forbidden actions (strictest wins)
* **Escalation triggers:** Union of all member escalation triggers
* **Audit retention:** Maximum of all member audit retention days (strictest wins)

Auto-derived cards are tagged with `card_source: "auto_derived"`. Cards can also be set manually (`"manual"`) or start from an auto-derived base and be customized (`"hybrid"`).

### Card inheritance

When a team's card changes, it does not retroactively modify member cards. Team cards and individual cards are independent — the team card represents the team's collective posture, which may differ from any individual member's card.

### Card history

Every card change is versioned. Retrieve the full history via:

```
GET /v1/teams/{team_id}/card/history
```

***

## Relationship to individual agent scores

Team Trust Ratings and individual Trust Ratings are related but independent:

| Aspect                | Individual Trust Rating                               | Team Trust Rating                                                 |
| --------------------- | ----------------------------------------------------- | ----------------------------------------------------------------- |
| **Unit**              | Single agent                                          | Team of 2--50 agents                                              |
| **Eligibility**       | 50 integrity checkpoints                              | 10 team risk assessments                                          |
| **Components**        | Integrity ratio, compliance, drift, traces, coherence | Coherence history, member quality, ops record, stability, density |
| **Data source**       | AIP checkpoints                                       | Team risk assessments                                             |
| **Update frequency**  | Hourly                                                | Every 6 hours + on-demand                                         |
| **Mutual dependency** | None (individual scores are independent)              | Member Quality reads individual scores (read-only)                |

The Member Quality component creates a one-way dependency: team scores read individual scores, but never write to them. Improving an individual member's score will improve the team's Member Quality component.

***

## ZK proofs for team reputation

Team reputation scores support the same cryptographic verification as individual scores. The verification endpoint returns proof data that independently confirms the score was computed correctly:

```
GET /v1/teams/{team_id}/reputation/verify
```

Team proofs chain individual proof attestations — the team's proof references the proof hashes of member scores used in the Member Quality computation, creating a verifiable dependency tree.

<Note>
  ZK proofs are available on Developer, Team, and Enterprise plans. Free-tier team assessments do not include proofs.
</Note>

***

## A2A trust extension for teams

The team reputation API includes a pre-built trust block for inter-team reputation sharing via A2A:

```json theme={null}
{
  "a2a_trust_extension": {
    "extension_uri": "https://mnemom.ai/ext/team-trust/v1",
    "provider": "mnemom",
    "score": 812,
    "grade": "AA",
    "confidence": "medium",
    "member_count": 5,
    "verified_url": "https://api.mnemom.ai/v1/teams/team-xyz/reputation/verify",
    "badge_url": "https://api.mnemom.ai/v1/teams/team-xyz/badge.svg",
    "methodology_url": "https://docs.mnemom.ai/concepts/team-reputation",
    "last_updated": "2026-02-25T06:00:00.000Z"
  }
}
```

Embed this in the team's A2A Agent Card to enable other agents and teams to make trust decisions about the team programmatically.

***

## API reference

The primary endpoint for fetching team reputation data:

```
GET /v1/teams/{team_id}/reputation
```

No authentication required for public teams. Returns the full score with all components.

**Response:**

```json theme={null}
{
  "team_id": "team-abc123",
  "team_name": "Support Pipeline Alpha",
  "score": 812,
  "grade": "AA",
  "confidence": "medium",
  "is_eligible": true,
  "components": [
    {
      "key": "coherence_history",
      "label": "Coherence History",
      "score": 880,
      "weight": 0.35,
      "weighted_score": 308,
      "factors": ["CQ trending upward over 12 assessments"]
    },
    {
      "key": "member_quality",
      "label": "Member Quality",
      "score": 790,
      "weight": 0.25,
      "weighted_score": 198,
      "factors": ["Tail-risk-weighted average across 5 members"]
    },
    {
      "key": "operational_record",
      "label": "Operational Record",
      "score": 850,
      "weight": 0.20,
      "weighted_score": 170,
      "factors": ["85% of assessments resulted in low/medium risk"]
    },
    {
      "key": "structural_stability",
      "label": "Structural Stability",
      "score": 720,
      "weight": 0.10,
      "weighted_score": 72,
      "factors": ["Low SR trend, 1 roster change in 30 days"]
    },
    {
      "key": "assessment_density",
      "label": "Assessment Density",
      "score": 640,
      "weight": 0.10,
      "weighted_score": 64,
      "factors": ["32 assessments, most recent 2 days ago"]
    }
  ],
  "total_assessments": 32,
  "last_assessed": "2026-02-23T10:00:00.000Z",
  "trend_30d": 18,
  "visibility": "public",
  "computed_at": "2026-02-25T06:00:00.000Z",
  "member_count": 5
}
```

For the complete API reference, see the [Teams API](/api-reference/team-overview).

***

## SDK usage

### TypeScript

```typescript theme={null}
import { fetchTeamReputation, fetchTeamReputationHistory } from '@mnemom/reputation';

// Get current team reputation
const reputation = await fetchTeamReputation('team-abc123');

if (reputation) {
  console.log(`Score: ${reputation.score}`);
  console.log(`Grade: ${reputation.grade}`);
  console.log(`Confidence: ${reputation.confidence}`);
  console.log(`30-day trend: ${reputation.trend_30d > 0 ? '+' : ''}${reputation.trend_30d}`);

  for (const component of reputation.components) {
    console.log(`  ${component.label}: ${component.score}/1000 (weight: ${component.weight})`);
  }
}

// Get weekly history for trend analysis
const history = await fetchTeamReputationHistory('team-abc123');
for (const snapshot of history) {
  console.log(`${snapshot.week_start}: ${snapshot.score} (${snapshot.grade})`);
}
```

### Python

```python theme={null}
import httpx

API_BASE = "https://api.mnemom.ai"

# Get current team reputation (public endpoint)
response = httpx.get(f"{API_BASE}/v1/teams/team-abc123/reputation")
reputation = response.json()

print(f"Score: {reputation['score']}")
print(f"Grade: {reputation['grade']}")
print(f"Confidence: {reputation['confidence']}")
print(f"30-day trend: {reputation['trend_30d']:+d}")

for component in reputation["components"]:
    print(f"  {component['label']}: {component['score']}/1000 (weight: {component['weight']})")

# Get weekly history
history = httpx.get(f"{API_BASE}/v1/teams/team-abc123/reputation/history")
for snapshot in history.json()["snapshots"]:
    print(f"{snapshot['week_start']}: {snapshot['score']} ({snapshot['grade']})")
```

***

## See also

* [Mnemom Trust Rating](/concepts/reputation-scores) -- Individual agent reputation scoring
* [Risk Assessment](/concepts/risk-assessment) -- Risk scoring model (input to team reputation)
* [Team Management Guide](/guides/team-management) -- Practical guide for creating and managing teams
* [Teams API](/api-reference/team-overview) -- Full API reference for team endpoints
* [Embeddable Badges](/guides/reputation-badges) -- Badge variants including team badges
* [Fleet Coherence](/concepts/fleet-coherence) -- Pairwise coherence data used in team scoring