Savings Report

kaddo savings turns the impact metrics into approximate time/effort/value estimates, so you can talk about Kaddo’s impact in terms non-technical stakeholders understand.

kaddo savings                  # Markdown to stdout (writes nothing) — scope: all
kaddo report savings           # alias
kaddo savings --json
kaddo savings --scope active
kaddo savings --output .kaddo/reports/savings-report.md
kaddo savings init             # write an editable .kaddo/savings.yml

Evidence-based estimate, not exact ROI. These figures are estimates, not accounting savings. Calibrate the assumptions with real team data.

Assumptions: .kaddo/savings.yml

Estimates = metrics + explicit assumptions. Run kaddo savings init to create an editable .kaddo/savings.yml (use --force to overwrite):

currency: USD
hourly_cost: 40
assumptions:
  context_preparation_minutes_saved_per_work_item: 30
  rework_hours_avoided_per_resolved_drift: 2
  onboarding_hours_saved_per_new_contributor: 4
  review_minutes_saved_per_work_item_with_ownership: 20
  clarification_minutes_saved_per_ready_work_item: 25
  architecture_discovery_hours_saved_when_graph_good: 3
team:
  expected_new_contributors_per_month: 1
  expected_work_items_per_month: 8

Without the file, Kaddo uses conservative defaults and says so.

What it estimates

Driver	Formula	Source
Context preparation	completed Work Items × minutes saved	impact evidence
Review effort	Work Items with ownership × minutes saved	impact evidence
Clarification reduction	Work Items with acceptance criteria × minutes saved	impact evidence
Onboarding	new contributors × hours × Context-Readiness multiplier (Low .25 → Very High 1.0)	impact evidence
Architecture discovery	hours × graph-quality multiplier (empty 0 → good 1.0)	impact evidence
Drift prevention	resolved drift warnings × rework_hours_avoided_per_resolved_drift	guard history

Estimated value = estimated hours saved × hourly_cost, shown as Estimated value (never “ROI”, “profit” or “real savings”). Defaults to scope: all like kaddo impact; --scope active measures only the active context.

Guard history and drift prevention

Drift prevention reflects recorded guard history (kaddo guard --record), with three distinct states:

State	Evidence	Drift prevention
No history recorded	Guard history: not available	not available
History, 0 resolved warnings	Guard history: available · Resolved drift warnings: 0	available, 0 h (“no resolved drift warnings recorded yet”)
History, resolved warnings	Resolved drift warnings: N	N × rework_hours_avoided_per_resolved_drift

Guard history available with zero resolved warnings still counts as available evidence, but drift-prevention savings remain 0 until at least one warning is resolved.

What it does NOT estimate

No exact ROI, no individual productivity, no per-person attribution, no team benchmarking, no time trends, no Jira/Linear/GitHub integration, no LLM, no dashboard. It never modifies code or knowledge, and writes nothing unless you pass --output.

Confidence

Each report carries a confidence level: Low (impact score < 60 or empty graph), Medium (solid evidence but default assumptions and/or no resolved drift history), High (strong evidence

• calibrated assumptions in .kaddo/savings.yml + recorded resolved drift warnings). Reaching High requires real drift-resolution evidence from kaddo guard --record.

Over MCP

The MCP server exposes it read-only: kaddo://savings-report (saved or in-memory) and the kaddo_generate_savings_report tool (format · scope · output) which writes only under .kaddo/reports/.

Using it with stakeholders

Pair it with the Impact Report: impact shows what is true about the knowledge; savings translates that into directional time and value. Always present it as an estimate to calibrate — that honesty is the point.