Trust Layer

{
  "general": {"score": 0.8},
  "coding": {"score": 0.9},
  "medical": {"score": 0.3}
}

[
  {"scope": "all"},
  {"scope": "belief_revision", "requires_evidence": true},
  {"scope": "information_only"}
]

kernle -s my-project trust seed

Seeded 4 trust assessments.

Current trust (4):
  stack-owner: 95%
  self: 80%
  web-search: 50%
  context-injection: 0%

kernle -s my-project trust list

Trust assessments (4):

  stack-owner
    General: [██████████] 95%
    Authority: all

  self
    General: [████████░░] 80%
    Authority: belief_revision (requires evidence)

  web-search
    General: [█████░░░░░] 50%
    medical: 30%
    Authority: information_only

kernle -s my-project trust show stack-owner

# Set general trust
kernle -s my-project trust set collaborator-agent 0.7

# Set domain-specific trust
kernle -s my-project trust set collaborator-agent 0.9 --domain coding

kernle -s my-project trust gate web-search suggest_belief

ALLOWED: Trust level sufficient for suggest_belief
  Trust level: 0.50
  Domain: general

kernle -s my-project trust gate web-search suggest_value_change

DENIED: Trust level insufficient for suggest_value_change
  Trust level: 0.50
  Domain: general

kernle -s my-project trust compute collaborator-agent

Computed trust for: collaborator-agent
  Score: [███████░░░] 72%
  Episodes: 15 (12.0 positive, 3.0 negative)

kernle -s my-project trust compute collaborator-agent --apply

kernle -s my-project trust chain unknown-agent stack-owner collaborator-agent

Transitive trust to: unknown-agent
  Chain: stack-owner -> collaborator-agent -> unknown-agent
  Domain: general
  Score: [█████░░░░░] 52%

  Hops:
    stack-owner: 95% direct, decay 1.00, cumulative 95%
    collaborator-agent: 72% direct, decay 0.85, cumulative 58%
    unknown-agent: 60% direct, decay 0.72, cumulative 52%

kernle -s my-project trust decay collaborator-agent 30

Applied trust decay for: collaborator-agent
  Days without interaction: 30
  Decay factor: 0.7397

  general: 53%
  coding: 67%

# 1. Check current trust — starts at DEFAULT_TRUST (0.5)
kernle -s my-project trust show new-colleague
# → Entity not found (uses default 0.5)

# 2. After initial positive interaction, set domain-specific trust
kernle -s my-project trust set new-colleague 0.6
kernle -s my-project trust set new-colleague 0.85 --domain coding

# 3. Record episodes about interactions (builds evidence base)
kernle -s my-project episode "Code review with new-colleague" "success" \
  --lesson "Caught a subtle race condition I missed" \
  --source-entity new-colleague

# 4. After several interactions, compute trust from evidence
kernle -s my-project trust compute new-colleague --apply
# → Score: 78% (based on 5 episodes: 4.5 positive, 0.5 negative)

# 5. Gate actions based on accumulated trust
kernle -s my-project trust gate new-colleague suggest_belief
# → ALLOWED (0.78 >= 0.30)

kernle -s my-project trust gate new-colleague suggest_value_change
# → DENIED (0.78 < 0.80)

# Trust a web API for factual data but not for value judgments
kernle -s my-project trust set external-api 0.7 --domain factual
kernle -s my-project trust set external-api 0.2 --domain values

# Trust a colleague highly for code but less for architecture
kernle -s my-project trust set senior-dev 0.9 --domain coding
kernle -s my-project trust set senior-dev 0.6 --domain architecture

# Gating checks the domain-specific score when available
kernle -s my-project trust gate external-api suggest_value_change
# → DENIED: uses 'values' domain score (0.20)

# 1. A belief arrives from a low-trust source
kernle -s my-project belief add "Redis is faster than Postgres for all queries" \
  --source-entity web-forum --source-type hearsay

# 2. Check trust for that source
kernle -s my-project trust show web-forum
# → General: 35%

# 3. The belief is accepted (35% > suggest_belief threshold of 30%)
# but gated from higher-trust operations

# 4. If the belief tries to change a value, it's blocked
kernle -s my-project trust gate web-forum suggest_value_change
# → DENIED (0.35 < 0.80)

# 1. Discover a source was unreliable
kernle -s my-project trust set unreliable-source 0.1

# 2. Find memories from that source
kernle -s my-project search "unreliable-source" --type belief

# 3. Weaken those beliefs (strength cascade propagates)
kernle -s my-project forget weaken <belief-id> --reason "Source trust dropped"
# Cascade flag propagates weakness to any memories derived from this belief

# List all trust assessments with scores
kernle -s my-project trust list

# Simulate what happens after 60 days of no interaction
kernle -s my-project trust decay collaborator-agent 60
# → general: 43% (was 72%)
# → coding: 58% (was 90%)

# Re-seed defaults if trust assessments were deleted
kernle -s my-project trust seed

from kernle import Kernle

k = Kernle(stack_id="my-stack")

# Seed default trust assessments
count = k.seed_trust()

# List all trust assessments
assessments = k.trust_list()
for a in assessments:
    entity = a["entity"]
    score = a["dimensions"].get("general", {}).get("score", 0)
    print(f"  {entity}: {int(score * 100)}%")

# Show trust for a specific entity
details = k.trust_show("stack-owner")

# Set trust score
k.trust_set("collaborator", domain="general", score=0.7)
k.trust_set("collaborator", domain="coding", score=0.9)

# Gate a memory operation
result = k.gate_memory_input(
    source_entity="web-search",
    action="suggest_belief",
    target="general"
)
if result["allowed"]:
    print("Action permitted")

# Compute trust from episode history
computed = k.trust_compute("collaborator", domain="general")
print(f"Computed: {computed['score']:.0%}")

# Transitive trust chain
chain_result = k.trust_chain(
    target="unknown-agent",
    chain=["stack-owner", "collaborator"],
    domain="general"
)

# Apply decay
decay_result = k.apply_trust_decay("collaborator", days_since_interaction=30)