Visibility Controls

Flock's visibility system provides zero-trust security for multi-agent systems—controlling which agents can see which artifacts on the blackboard.

Think of it like classified documents: not everyone in an organization can see every document. Field agents see different data than executives, and customer data stays isolated between tenants.

Unlike other frameworks, Flock has security built-in from day one.

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What is Visibility?

Visibility determines which agents can consume an artifact from the blackboard.

• Producer-controlled - The agent publishing data decides who can see it
• Enforced automatically - Flock checks visibility before scheduling agents
• Zero-trust architecture - Explicit access control, not "hope-based security"
• No agent ever sees unauthorized data - Security violations are impossible

Key principle: The agent producing the artifact controls who can consume it.

---

The Five Visibility Types

Here's how visibility controls work:

graph TB
    subgraph "📤 Artifact Published"
        Artifact[📋 Artifact<br/>with Visibility Control]
    end

    subgraph "🔐 Visibility Check"
        Check{Visibility Type?}
    end

    subgraph "🟢 Public Visibility"
        Public[✅ All agents can access]
        A1[Agent 1] & A2[Agent 2] & A3[Agent 3]
    end

    subgraph "🔵 Private Visibility"
        Private[✅ Only allowlist agents]
        A4[Agent X ✅<br/>in allowlist]
        A5[Agent Y ❌<br/>blocked]
    end

    subgraph "🟡 Tenant Visibility"
        Tenant[✅ Only same tenant]
        A6[Agent A<br/>tenant: customer-1 ✅]
        A7[Agent B<br/>tenant: customer-2 ❌]
    end

    subgraph "🟣 Labelled Visibility"
        Labels[✅ Must have required labels]
        A8[Agent with<br/>role:admin ✅]
        A9[Agent without<br/>labels ❌]
    end

    subgraph "🔴 Time Visibility"
        Time[✅ Only within time window]
        A10[Agent<br/>within window ✅]
        A11[Agent<br/>window expired ❌]
    end

    Artifact --> Check

    Check -->|PublicVisibility| Public
    Public --> A1 & A2 & A3

    Check -->|PrivateVisibility| Private
    Private --> A4
    Private -.blocks.-> A5

    Check -->|TenantVisibility| Tenant
    Tenant --> A6
    Tenant -.blocks.-> A7

    Check -->|LabelledVisibility| Labels
    Labels --> A8
    Labels -.blocks.-> A9

    Check -->|TimeVisibility| Time
    Time --> A10
    Time -.blocks.-> A11

    style Artifact fill:#60a5fa,stroke:#333,stroke-width:3px,color:#000
    style Check fill:#4f46e5,stroke:#333,stroke-width:2px,color:#fff
    style Public fill:#10b981,stroke:#333,stroke-width:2px,color:#000
    style Private fill:#3b82f6,stroke:#333,stroke-width:2px,color:#fff
    style Tenant fill:#eab308,stroke:#333,stroke-width:2px,color:#000
    style Labels fill:#8b5cf6,stroke:#333,stroke-width:2px,color:#fff
    style Time fill:#ef4444,stroke:#333,stroke-width:2px,color:#fff

Access Control Flow:

1. Artifact Published - Producer sets visibility type
2. Visibility Check - Orchestrator validates access for each potential consumer
3. Allowed Agents - Only authorized agents receive the artifact
4. Blocked Agents - Unauthorized agents never see the artifact (zero-trust)

Key Security Properties: - ✅ Producer-Controlled - Publishing agent sets access rules - ✅ Automatic Enforcement - No manual checks needed - ✅ Zero-Trust - Explicit allow, not implicit deny - ✅ Audit Trail - All access checks logged in traces

1. PublicVisibility (Default)

Everyone can see the artifact.

from flock.visibility import PublicVisibility

agent = (
    flock.agent("reporter")
    .consumes(Draft)
    .publishes(Article, visibility=PublicVisibility())
)

Use when: - Shared data across all agents - Public announcements - Non-sensitive information - Default behavior (no visibility specified)

Example: Blog posts, public reports, shared metrics

---

2. PrivateVisibility (Allowlist)

Only specified agents can see the artifact.

from flock.visibility import PrivateVisibility

field_agent = (
    flock.agent("field_agent")
    .consumes(Mission)
    .publishes(
        RawIntelligence,
        visibility=PrivateVisibility(agents={"intelligence_analyst"})
    )
)

Use when: - Sensitive data for specific processors - Explicit allowlist access control - HIPAA compliance (patient data → treating physician) - One-to-one data handoff

Example: Medical records, financial transactions, classified intelligence

---

3. TenantVisibility (Multi-Tenancy)

Only agents belonging to the same tenant can see the artifact.

from flock.visibility import TenantVisibility

analyzer = (
    flock.agent("analyzer")
    .consumes(CustomerEvent)
    .publishes(
        Analysis,
        visibility=TenantVisibility(tenant_id="customer_123")
    )
)

Use when: - SaaS platforms with multiple customers - Complete data isolation between tenants - Customer A can't see Customer B's data - Multi-organization systems

Example: SaaS customer data, multi-tenant analytics, isolated workspaces

---

4. LabelledVisibility (RBAC)

Only agents with required labels can see the artifact.

from flock.visibility import LabelledVisibility, AgentIdentity

# Agent with security clearance
analyst = (
    flock.agent("analyst")
    .identity(AgentIdentity(
        name="analyst",
        labels={"clearance:secret", "role:intelligence"}
    ))
    .consumes(RawIntelligence)
    .publishes(
        AnalysisReport,
        visibility=LabelledVisibility(required_labels={"clearance:secret"})
    )
)

Use when: - Role-Based Access Control (RBAC) - Multi-level security clearances - Tiered access (free vs pro users) - Organizational hierarchies

Example: Security clearances, subscription tiers, organizational roles

---

5. AfterVisibility (Time-Delayed)

Artifact becomes visible after a time delay.

from datetime import timedelta
from flock.visibility import AfterVisibility, PublicVisibility

pr_team = (
    flock.agent("pr_team")
    .consumes(NewsStory)
    .publishes(
        PressRelease,
        visibility=AfterVisibility(
            ttl=timedelta(hours=24),
            then=PublicVisibility()
        )
    )
)

Use when: - Press embargoes - Scheduled releases - Quarterly report delays - Time-sensitive disclosures

Example: Earnings reports, press releases, clinical trial results

---

Agent Identity

Agents need identities to interact with visibility controls:

from flock.visibility import AgentIdentity

agent = (
    flock.agent("analyst")
    .identity(AgentIdentity(
        name="analyst",
        labels={"clearance:secret", "role:analyst", "tier:pro"}
    ))
    .consumes(SensitiveData)
    .publishes(Report)
)

Identity components: - name - Unique agent identifier - labels - Set of access control labels

Label format convention: category:value - clearance:secret - Security clearance level - role:analyst - Organizational role - tier:pro - Subscription tier - region:us-east - Geographic scope

---

How Visibility Enforcement Works

Publish-Time Assignment

When an agent publishes an artifact, visibility is set:

# Producer controls visibility
await flock.publish(
    SensitiveData(value="secret"),
    visibility=PrivateVisibility(agents={"trusted_agent"})
)

Scheduling-Time Check

Before scheduling an agent, Flock checks visibility:

# Flock's internal logic (you don't write this)
for agent in potential_consumers:
    if artifact.visibility.allows(agent.identity):
        schedule_agent(agent, artifact)  # ✅ Allowed
    else:
        skip_agent(agent)  # 🔒 Blocked

Result: No agent ever sees data it shouldn't access.

---

Real-World Use Cases

Healthcare (HIPAA Compliance)

Challenge: Patient data must only be accessible to treating physicians.

from flock.visibility import PrivateVisibility, LabelledVisibility

# Patient record only for treating physician
doctor = (
    flock.agent("doctor")
    .consumes(PatientVisit)
    .publishes(
        PatientRecord,
        visibility=PrivateVisibility(agents={"treating_physician"})
    )
)

# Lab results for anyone with medical clearance
lab_tech = (
    flock.agent("lab_tech")
    .identity(AgentIdentity(name="lab_tech", labels={"role:medical"}))
    .consumes(LabOrder)
    .publishes(
        LabResults,
        visibility=LabelledVisibility(required_labels={"role:medical"})
    )
)

Financial Services (Multi-Tenancy)

Challenge: Complete data isolation between customers.

from flock.visibility import TenantVisibility

# Each customer's portfolio is isolated
trading_agent = (
    flock.agent("trader")
    .consumes(MarketData)
    .publishes(
        CustomerPortfolio,
        visibility=TenantVisibility(tenant_id=customer.id)
    )
)

# Customer A's agent can't see Customer B's data

Enterprise SaaS (Tiered Access)

Challenge: Free users see basic features, pro users see advanced analytics.

from flock.visibility import LabelledVisibility

# Basic reports for free and pro users
analyzer = (
    flock.agent("analyzer")
    .consumes(UserActivity)
    .publishes(
        BasicReport,
        visibility=LabelledVisibility(
            required_labels={"tier:free", "tier:pro"}  # Either label works
        )
    )
)

# Advanced analytics only for pro users
advanced_analyzer = (
    flock.agent("advanced")
    .identity(AgentIdentity(labels={"tier:pro"}))
    .consumes(UserActivity)
    .publishes(
        AdvancedAnalytics,
        visibility=LabelledVisibility(required_labels={"tier:pro"})
    )
)

Government/Intelligence (Security Clearances)

Challenge: Multi-level security clearances (Unclassified → Secret → Top Secret).

from flock.visibility import LabelledVisibility, AgentIdentity

# Field agent collects classified intel
field_ops = (
    flock.agent("field_ops")
    .identity(AgentIdentity(labels={"clearance:field_ops"}))
    .consumes(Mission)
    .publishes(
        ClassifiedIntel,
        visibility=LabelledVisibility(required_labels={"clearance:secret"})
    )
)

# Only analysts with secret clearance can see it
analyst = (
    flock.agent("analyst")
    .identity(AgentIdentity(labels={"clearance:secret"}))
    .consumes(ClassifiedIntel)
    .publishes(ThreatAssessment)
)

👉 See complete intelligence example

Press & Media (Embargoes)

Challenge: Press releases visible only after embargo period.

from datetime import timedelta
from flock.visibility import AfterVisibility, PublicVisibility

# Embargo for 7 days, then public
pr_team = (
    flock.agent("pr_team")
    .consumes(NewsStory)
    .publishes(
        PressRelease,
        visibility=AfterVisibility(
            ttl=timedelta(days=7),
            then=PublicVisibility()
        )
    )
)

---

Comparison to Other Frameworks

Traditional Frameworks

# ❌ NO built-in security
# Every agent sees everything on the blackboard
agent1.publishes(SensitiveData(...))
# Any agent can consume it - hope they don't!

# ❌ "Bring your own" security
# You implement access control yourself
if user.has_permission("read_sensitive"):
    process(data)  # Manual checks everywhere

Flock

# ✅ Producer-controlled access
agent1.publishes(
    SensitiveData(...),
    visibility=PrivateVisibility(agents={"trusted_agent"})
)
# Only trusted_agent can consume - enforced automatically!

# ✅ Zero-trust by default
# No agent sees unauthorized data - impossible to bypass

---

Advanced Patterns

Multi-Level Security

Create hierarchical clearance levels:

# Unclassified → Confidential → Secret → Top Secret
junior_analyst = flock.agent("junior").identity(AgentIdentity(
    labels={"clearance:confidential"}
))

senior_analyst = flock.agent("senior").identity(AgentIdentity(
    labels={"clearance:secret"}
))

# Junior can't see secret data
.publishes(SecretReport, visibility=LabelledVisibility(
    required_labels={"clearance:secret"}
))

Organizational Hierarchy

Implement reporting structures:

# Junior analysts can't see senior work
junior = flock.agent("junior").identity(AgentIdentity(
    labels={"level:junior"}
))

# Senior work requires senior label
senior = flock.agent("senior").identity(AgentIdentity(
    labels={"level:senior"}
)).publishes(
    SeniorAnalysis,
    visibility=LabelledVisibility(required_labels={"level:senior"})
)

Time-Based Access Expiry

Data becomes more restricted over time:

# Public for 1 hour, then private archival
.publishes(
    TemporaryData,
    visibility=AfterVisibility(
        ttl=timedelta(hours=1),
        then=PrivateVisibility(agents={"archiver"})
    )
)

Combined Patterns

Mix visibility types for complex requirements:

# Tenant-specific + role-based
.publishes(
    CustomerReport,
    visibility=TenantVisibility(tenant_id="customer_123")
    # AND agent needs role:analyst label (custom logic)
)

---

Security Best Practices

✅ Do

• Principle of Least Privilege - Give minimum necessary access
• Use PrivateVisibility for sensitive data - Explicit allowlists
• Enable audit logging - Track who accessed what (via tracing)
• Review access regularly - Periodically audit agent permissions
• Test security boundaries - Verify agents can't bypass visibility
• Document security model - Explain why each visibility choice was made

❌ Don't

• Don't make everything public - Default to restricted
• Don't rely on single layer - Defense in depth (visibility + identity + audit)
• Don't skip identity assignment - Agents need identities for RBAC
• Don't forget to test - Verify access control works
• Don't set-and-forget - Access needs regular review
• Don't ignore audit logs - Monitor for security violations

---

Debugging Visibility Issues

Agent Not Triggering?

Check visibility match:

# Enable tracing to see if agent was blocked
export FLOCK_AUTO_TRACE=true
export FLOCK_TRACE_FILE=true

# Run and check agent scheduling
await flock.publish(artifact)
await flock.run_until_idle()

# Query DuckDB for visibility blocks
import duckdb
conn = duckdb.connect('.flock/traces.duckdb')
# Check if agent was considered but blocked

Common issues: - Agent missing required labels - Agent not in private allowlist - Tenant ID mismatch - Time delay not elapsed

Verify Agent Identity

# Print agent identity
print(agent.identity)
# AgentIdentity(name='analyst', labels={'clearance:secret'})

# Check if identity matches visibility
artifact_visibility = PrivateVisibility(agents={"analyst"})
can_access = artifact_visibility.allows(agent.identity)
print(f"Can access: {can_access}")

Check Artifact Visibility

# Retrieve artifact and check visibility
artifacts = await flock.store.get_artifacts_by_type("SensitiveData")
for artifact in artifacts:
    print(f"Visibility: {artifact.visibility}")
    print(f"Type: {type(artifact.visibility).__name__}")

---

Common Patterns

Public by Default, Private Exceptions

# Most data is public
reporter = flock.agent("reporter").publishes(Article)  # PublicVisibility (default)

# Sensitive data is private
auditor = flock.agent("auditor").publishes(
    AuditReport,
    visibility=PrivateVisibility(agents={"compliance_officer"})
)

Progressive Disclosure

# Start private, become public later
.publishes(
    QuarterlyReport,
    visibility=AfterVisibility(
        ttl=timedelta(days=90),  # 90-day embargo
        then=PublicVisibility()
    )
)

Multi-Tenant Isolation

# Complete isolation between tenants
for tenant in tenants:
    tenant_agent = flock.agent(f"agent_{tenant.id}").publishes(
        TenantData,
        visibility=TenantVisibility(tenant_id=tenant.id)
    )

Clearance Hierarchy

# Confidential < Secret < Top Secret
clearance_levels = ["confidential", "secret", "top_secret"]

for level in clearance_levels:
    agent = flock.agent(f"agent_{level}").identity(
        AgentIdentity(labels={f"clearance:{level}"})
    ).publishes(
        ClassifiedData,
        visibility=LabelledVisibility(required_labels={f"clearance:{level}"})
    )

---

Next Steps

• Agents Guide - Learn how agents interact with visibility
• Blackboard Architecture - Understand artifact flow
• Dashboard - Visualize visibility controls
• Complete Example - Intelligence agency with all 5 visibility types

---

Complete Example

Here's everything together—a secure multi-agent system:

import asyncio
from datetime import timedelta
from pydantic import BaseModel, Field
from flock import Flock, flock_type
from flock.visibility import (
    PublicVisibility,
    PrivateVisibility,
    TenantVisibility,
    LabelledVisibility,
    AfterVisibility,
    AgentIdentity
)

# Define artifacts
@flock_type
class Mission(BaseModel):
    mission_id: str
    objective: str

@flock_type
class RawIntelligence(BaseModel):
    mission_id: str
    observations: list[str]
    sensitivity: str

@flock_type
class AnalysisReport(BaseModel):
    mission_id: str
    threat_assessment: str
    confidence: float

@flock_type
class ExecutiveBrief(BaseModel):
    mission_id: str
    summary: str
    next_steps: list[str]

# Create orchestrator
flock = Flock("openai/gpt-4.1")

# Field agent - collects classified intel
field_agent = (
    flock.agent("field_agent")
    .identity(AgentIdentity(name="field_agent", labels={"clearance:field_ops"}))
    .consumes(Mission)
    .publishes(
        RawIntelligence,
        visibility=PrivateVisibility(agents={"analyst"})  # 🔒 Only analyst sees
    )
)

# Analyst - requires secret clearance
analyst = (
    flock.agent("analyst")
    .identity(AgentIdentity(name="analyst", labels={"clearance:secret"}))
    .consumes(RawIntelligence)
    .publishes(
        AnalysisReport,
        visibility=LabelledVisibility(required_labels={"clearance:secret"})  # 🏷️ Need clearance
    )
)

# Director - creates public brief
director = (
    flock.agent("director")
    .identity(AgentIdentity(name="director", labels={"clearance:secret", "role:leadership"}))
    .consumes(AnalysisReport)
    .publishes(ExecutiveBrief, visibility=PublicVisibility())  # 🌍 Everyone sees
)

# Use it
async def main():
    # Start mission
    await flock.publish(Mission(
        mission_id="OP-BLACKBIRD-2025",
        objective="Investigate cyber threats"
    ))

    # Cascade through security layers
    await flock.run_until_idle()

    # Get public brief
    briefs = await flock.store.get_by_type(ExecutiveBrief)
    print(f"Executive Brief: {briefs[0].summary}")

asyncio.run(main())

What happened: 1. ✅ Mission published (public) 2. ✅ field_agent produces RawIntelligence (private to analyst) 3. ✅ analyst produces AnalysisReport (requires secret clearance) 4. ✅ director produces ExecutiveBrief (public to leadership) 5. ✅ All visibility controls enforced automatically

Security guarantees: - 🔒 Only analyst sees RawIntelligence - 🏷️ Only agents with secret clearance see AnalysisReport - 🌍 Everyone sees ExecutiveBrief - ✅ No agent can bypass visibility

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Ready to secure your agents? Start with the Quick Start Guide or explore the complete intelligence example.