Agent Traceability

Kōdo is the first programming language with built-in support for tracking AI agent authorship and enforcing trust policies. This enables organizations to maintain accountability over AI-generated code.

Annotations

@authored_by

Declares who wrote a function — human or AI agent:

@authored_by(agent: "claude")
fn ai_generated() -> Int {
    return 42
}

@confidence

Declares how confident the author is in the correctness of the code, on a scale from 0.0 to 1.0:

@confidence(0.95)
fn well_tested() -> Int {
    return 42
}

@reviewed_by

Declares that a human has reviewed the code:

@reviewed_by(human: "alice")
fn human_approved() -> Int {
    return 42
}

@security_sensitive

Marks a function as security-sensitive, requiring formal contracts:

@security_sensitive
fn validate_input(value: Int) -> Bool
    requires { value > 0 }
{
    return true
}

Note: Contract expressions currently support integer and boolean comparisons. String comparisons in requires/ensures are not yet supported.

Trust Policies

Low Confidence Review (E0260)

Functions with @confidence(X) where X < 0.8 must have @reviewed_by(human: "..."):

// ERROR: @confidence(0.5) < 0.8 without review
@confidence(0.5)
fn risky() -> Int { return 42 }

// OK: low confidence but reviewed
@confidence(0.5)
@reviewed_by(human: "alice")
fn reviewed_risky() -> Int { return 42 }

Security-Sensitive Contracts (E0262)

Functions marked @security_sensitive must have at least one requires or ensures clause.

Confidence Propagation

Kōdo computes transitive confidence for each function. A function’s computed confidence is the minimum of:

• Its own declared @confidence (defaults to 1.0 if not specified)
• The computed confidence of every function it calls

This means confidence propagates through the call chain — a function is only as trustworthy as its least trustworthy dependency.

Module Confidence Threshold (E0261)

Set min_confidence in the meta block to enforce a minimum confidence level:

module secure_app {
    meta {
        purpose: "A security-critical application"
        min_confidence: "0.9"
    }

    @confidence(0.5)
    @reviewed_by(human: "alice")
    fn weak_link() -> Int { return 1 }

    fn main() -> Int {
        return weak_link()  // ERROR E0261: module confidence 0.50 < threshold 0.90
    }
}

Confidence Report

Use kodoc confidence-report to inspect confidence across a module:

kodoc confidence-report my_module.ko

# Output:
# Confidence Report for module `my_module`
# ============================================================
# Overall confidence: 0.50
#
# Function                       Declared   Computed
# ------------------------------------------------------------
# weak_link                          0.50       0.50
# main                               1.00       0.50

For JSON output (suitable for AI agent consumption):

kodoc confidence-report my_module.ko --json