Lag 5 kjører ETTER transformasjon (lag 4) og FØR en kandidat-endring skrives til
en KB-fil. Den fanger regresjons-klassen: en status-påstand «korrigert» mot en
tilfeldig sitert side og stille auto-applyet (den kjente agentic-retrieval-
regresjonen — hovedkontekst måtte rette manuelt).
Regel (spec §21): status-påstander (GA/preview/versjon/pris) flagges ALLTID for
operatør, aldri auto-applyet — uansett hvor sikker evidensen ser ut.
- lib/verify-out.mjs: ren klassifiserer, null deps (speiler decisions-io).
detectStatusClaim(text) → {isStatus, kinds}; classifyChange(change) →
{verdict: flagged|auto-applied, status_claim, reasons}. Tre flag-regler:
status-gate (§21) · adversarial refutering · autoritets-mismatch (regresjonens
rotårsak). Konservativ med vilje: ved tvil flagges. SKRIVER ALDRI.
- Fixtur tests/fixtures/kb-update/agentic-retrieval-regression.json: den kjente
regresjonen (flat «GA» mot nyansert «delvis GA … resten preview»).
- TDD: 13 tester før kode, inkl. import-invariant (ingen write-utils).
- Wiret i kb-update.md §4 c2 (lag 5 mellom identifiser-endring og skriv).
Kriterium møtt: fixtur → flagged:true, ikke auto-applied.
Tester: validate 239 · kb-update 95 (+13) · kb-eval 13 · kb-integrity 115/115.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01REiKFhP4w6xGXXqWKpPCJJ
Synthetic ROS-analyse output for "Acme Kunde-chatbot" (Acme Kommune)
following the same pattern as security-assessment, cost-estimation,
ai-act and summary fixtures. Satisfies all 29 assertions in
tests/test-ros-output.sh:
- 8 phases (Fase 1-8) plus Ledelsessammendrag
- 12 trusler i T-XXX-NN format (MAESTRO + OWASP-mapping)
- 9 risikoer i R-N format
- 10 tiltak i M-N format
- 7 ROS-dimensjoner med X/5-scoring
- 5x5 risikomatrise + restrisiko-tabell
- NS 5814 + ISO 31000 metodikk-referanser
- AI Act, GDPR, OWASP regulatoriske referanser
- MAESTRO + supply-chain referanser (Vedlegg O coverage)
Tar bort den siste pre-eksisterende run-e2e-feilen
(`bash tests/run-e2e.sh` exits 0).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Add /ultraresearch-local for structured research combining local codebase
analysis with external knowledge via parallel agent swarms. Produces research
briefs with triangulation, confidence ratings, and source quality assessment.
New command: /ultraresearch-local with modes --quick, --local, --external, --fg.
New agents: research-orchestrator (opus), docs-researcher, community-researcher,
security-researcher, contrarian-researcher, gemini-bridge (all sonnet).
New template: research-brief-template.md.
Integration: --research flag in /ultraplan-local accepts pre-built research
briefs (up to 3), enriches the interview and exploration phases. Planning
orchestrator cross-references brief findings during synthesis.
Design principle: Context Engineering — right information to right agent at
right time. Research briefs are structured artifacts in the pipeline:
ultraresearch → brief → ultraplan --research → plan → ultraexecute.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
