METRICL5 · Agentic Workflow Health

Agent Intent-First Index

The percentage of agent-authored PRs where CHI approval preceded the agent's first commit.

Abbreviation
AIFI
Layer
L5 · Agentic Workflow Health
Range
0 – 100
Direction
Higher is better
Target metric — not yet computed

This page describes the intended design. It requires comparing agent-driven CHI approval timing against the agent's first commit, which isn't built yet. It doesn't appear on your dashboard yet, and no org currently has a live value for it.

Formula

AIFIformula
AIFI = (agent-authored PRs where
            CHI approval date
            < agent first commit date
  ÷ total agent-authored PRs)
  × 100

Thresholds

≥ 80

Agents executing within approved scope

≥ 60

Orchestration gaps — investigate workflows

< 60

Autonomous generation without scope — highest risk

Reading it

The agentic equivalent of IFR. AIFI measures whether AI agents are being invoked against architect-approved Change Intentions before generating code — not after. A high AIFI means the orchestration layer ensures an approved CHI exists before the agent starts. A low AIFI means agents are autonomous code generators operating without pre-approved architectural scope: the highest-risk agentic deployment pattern.

IFR and AIFI look similar but require different remediation. Low human IFR is a culture and process problem — developers are not following the intent-first workflow. Low AIFI is an orchestration tooling problem — the system that spawns agents is not checking for approved CHI scope before dispatch. The fix is not developer education; it is workflow integration: require get_approved_chi() as a pre-start check in the orchestration layer.

AIFI rising after rkito MCP integration is evidence that the integration is working as intended. Agents invoked with an approved CHI in scope know what they are authorised to change before writing a single line. They operate as specification executors, not autonomous generators. This is the distinction that separates governed agentic development from ungoverned agentic development.

How rkito produces it

Agent-authored PR attribution uses commit signatures and MCP access logs to identify agent-generated branches. CHI approval timestamps are then compared against the earliest agent commit on that branch. AIFI is the percentage of agent-authored structural PRs that are AIFI HITs, computed per sprint.

  1. 01

    Agent-authored PR identified

    Commit signatures and MCP access logs confirm agent authorship of the branch

  2. 02

    CHI approval timestamp retrieved for the branch

    rkito resolves the Change Intention linked to the branch and reads its architect approval timestamp

  3. 03

    Agent first commit timestamp retrieved for the branch

    Earliest agent commit on the branch is recorded as the agent start time

  4. 04
    HIT

    CHI approval date < first commit date

    AIFI HIT — agent invoked within approved architectural scope

  5. 05
    MISS

    CHI approved after first commit, or no CHI

    AIFI MISS — agent operated as autonomous generator without pre-approved scope

  6. 06

    AIFI = % of agent-authored structural PRs that are AIFI HITs, per sprint

    Hit rate reported per sprint and trended on the org dashboard

Who reads it

Engineering LeadershipVP EngSpecification executors vs. autonomous generators

AIFI shows whether the team uses agents as specification executors (high AIFI) or autonomous generators (low AIFI). These are fundamentally different risk profiles.

Design AuthorityArchitectAgent sessions starting with approved design context

AIFI is the signal for whether agent sessions start with approved design context. Low AIFI = agents are making architectural decisions without review.

How it misleads

What to do at each threshold

Step-by-step response playbook for each signal state.

Green≥ 80Confirm depth

Agents are being invoked within approved architectural scope. Confirm MCPCAR is also high — agents should be loading design context, not just having a CHI on record.

  1. Confirm MCPCAR is also high — agents should be loading design context, not just having a CHI technically on record. A high AIFI with low MCPCAR means the pre-start check exists but the context load does not. The CHI is approved; the agent never read it.
Yellow≥ 60Integrate pre-start check

Identify which agent workflows are starting without approved CHIs. Integrate the pre-start check in the orchestration layer.

  1. Identify which agent workflows are starting without approved CHIs. Integrate get_approved_chi() as a mandatory pre-start check in the orchestration layer.
Red< 60Fix the orchestration layer

Agents are operating as autonomous generators without design scope. Require the orchestration layer to call draft_chi and halt if no approved CHI exists before agent startup.

  1. Require the orchestration layer to call draft_chi and halt if no approved CHI exists before agent startup. This is an orchestration tooling problem, not a culture problem — the fix is a code change, not an announcement.

What is your org's AIFI?

rkito calculates AIFI automatically from agent PR attribution, CHI approval timestamps, and first commit dates. Connect your repo and see your agentic governance posture within minutes.