# Fraysaxii Openclaw Akos Intent Ranked Regression Craft > Intent-Ranked Regression Craft - Skill: `tomevault-io/fraysaxii-openclaw-akos-intent-ranked-regression-craft` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/fraysaxii-openclaw-akos-intent-ranked-regression-craft` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/fraysaxii-openclaw-akos-intent-ranked-regression-craft/raw - Safety review: pending (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/fraysaxii-openclaw-akos-intent-ranked-regression-craft --- # Intent-Ranked Regression Craft > Minted 2026-06-05 from the operator's framing: *"not mechanical — take all my > intents, use cases, logic, scenarios, interactions (past/present/future), make a > ranking system, research inside and outside, review it, then regress."* This is > the **value layer** above the mechanical inter-wave regression (which checks *is > everything wired?*); this layer asks *is what I care about most still served?* ## Why this exists (vs the mechanical sweep) `akos-inter-wave-regression.mdc` runs 13 structural dimensions at ~equal weight. That answers integrity, not **priority**. When attention is scarce (operator review minutes; agent context budget), you want the highest-stakes surfaces checked first and deepest. External practice converges here: - **FMEA / RPN** (Jama, SixSigma, testRigor 2026): rank failure modes by Severity × Occurrence × Detection; **severity-first override** — a catastrophic surface is actioned regardless of composite score. - **WSJF** (SAFe / Reinertsen): Cost of Delay = Business-Value + Time-Criticality + Risk-Reduction; the right altitude for an **initiative-portfolio** regression. - **TIA + Predictive Test Selection** (Microsoft, Meta, Fowler): bound the candidate set by what changed, rank by fault-likelihood, keep the **full sweep as a periodic safety net** (never delete it). ## The model (SSOT in code) `akos/hlk_intent_ranked_regression.py` — 7 intent tiers + N surfaces + ICS. `scripts/intent_ranked_regression.py --rank` prints the ranked sweep order. ``` ICS = 3*intent_value + 2*time_criticality + 2*risk_reduction + 1*detection_gap ``` - `intent_value` (1-5) = max value of the intent tiers the surface serves. - `time_criticality` (1-5) = does delay cost? (before first sale / incorporation). - `risk_reduction` (1-5) = blast radius if it breaks. - `detection_gap` (1-5) = FMEA Detection **inverted** — 5 means no always-on gate would catch a regression here (so it deserves manual eyes); 1 means a strong gate already does. - `severity_first` = FMEA Action-Priority override: existence-critical surfaces (legal/fiscal IT-2, governance-integrity IT-3) with a known live gap lead the queue regardless of ICS. ## The loop (both seats) 1. **Distil the intent corpus** (thinking seat): sweep operator-scratchpad, RICE-ranked `OPERATOR_INBOX.md`, `USE_CASE_ARCHIVE.csv`, open `OPS_REGISTER` severities, `INITIATIVE_REGISTRY`. Update tier weights only with evidence — never invent priority. Re-derive when the portfolio shifts materially. 2. **Score / re-score surfaces** (either seat): edit the surfaces in the SSOT module; `--self-test` must stay green. 3. **Run in ICS order** (execution seat): `--rank` gives the ordered probe list. Run top-down; stop-early is allowed only when remaining surfaces are all low-ICS AND green so far. 4. **Attribute every finding** (thinking seat) — the load-bearing craft move: - **new** = this session's diff caused it → rework-now. - **pre-existing** = drift that predates this session → fix-now only if high-ICS + low-effort + reversible (FMEA severity-first); else defer-OPS with owner. - **known-deferred** = already has an OPS row + ETA → cite it, do not re-litigate. 5. **Disposition** via the inter-wave 5-option enum (rework-now / forward-charter / defer-OPS / accept-as-canon / escalate-to-blocker). Never ad-hoc. 6. **Mint findings + (if high value) harden the method** so the next regression is cheaper — that is this discipline eating its own tail. ## Anti-patterns - **AP1 — Flat failure lists.** A release-gate "9 failed" is not a regression result; rank + attribute the 9, or you have only noise. - **AP2 — Blaming your own diff for inherited drift** (or the reverse). Attribution is mandatory; it is the difference between "I regressed X" and "X was already red". - **AP3 — Deleting the safety net.** The ranked sweep *supplements* the full mechanical sweep / release-gate; it never replaces it (TIA safety-fallback). - **AP4 — Inventing intent weights.** Every tier value cites scratchpad / inbox / OPS / registry evidence. No evidence, no weight change. - **AP5 — RPN-only blindness.** Honour severity-first: an existence-critical surface leads even if its composite ICS is not the maximum. ## Worked example `docs/wip/planning/88-cross-area-ops-wiring-review-discipline/reports/intent-ranked-regression-2026-06-05.md` — the 2026-06-05 run: 3552 pass / 9 fail, attributed to **0 new regressions**, 1 high-intent pre-existing drift fixed-now (the `area_governance` pattern-class enum lag from I93), 8 known/deferred dispositioned. ## Cross-references - SSOT model: `akos/hlk_intent_ranked_regression.py` - Runbook: `scripts/intent_ranked_regression.py` - Draft rule: `.cursor/rules/akos-intent-ranked-regression.mdc` - Sister discipline (the safety net): `.cursor/rules/akos-inter-wave-regression.mdc` + `.cursor/skills/inter-wave-regression-craft/SKILL.md` - Disposition enum: `.cursor/rules/akos-inline-ratification.mdc` --- > Source: [FraysaXII/openclaw-akos](https://github.com/FraysaXII/openclaw-akos) — distributed by [TomeVault](https://tomevault.io).