skillguard/.agents/memory/MEMORY.md

- [lucide-react icon name collisions](lucide-icon-name-collisions.md) — `Badge`/`Activity` from lucide collide with shadcn/ui Badge and React 19 Activity; import Badge from ui, Activity from lucide.
- [OpenAI gpt-5 temperature](openai-temperature-gpt5.md) — gpt-5* reject `temperature != 1`; omit temperature in OpenAI-compatible clients or AI analysis silently fails.
SkillGuard: complete frontend wiring and harden backend Original task: build "SkillGuard", a German web app to audit agent skills on two axes (IT-Sicherheit, Datenschutz) with static rule engine + Replit-independent AI analysis configured via an admin backend. This session: - Fixed frontend TS errors: lucide-react name collisions (Badge from ui, Activity from lucide), widened apiType to AiProviderApiType, added queryKey to useGetScan. - Verified all pages render in German (Dashboard, Prüfen, Bericht, Verlauf, Admin) and the full scan flow works end-to-end (malicious sample -> verdict block). Code-review-driven hardening: - POST /api/scans now returns the full ScanDetail (files + findings) to match the OpenAPI contract, instead of only the summary. - AI provider error bodies are redacted (token, Bearer, sk- patterns) before being returned/persisted, and provider fetches now have a 60s timeout. - ZIP parsing now enforces limits (max files, total + per-file size) to mitigate zip-bomb DoS. Updated replit.md (project overview, decisions, gotchas) and added a memory note on lucide-react icon name collisions. 2026-06-08 14:59:17 +00:00			- [lucide-react icon name collisions](lucide-icon-name-collisions.md) — `Badge`/`Activity` from lucide collide with shadcn/ui Badge and React 19 Activity; import Badge from ui, Activity from lucide.
Task #2: Skill mit konfigurierter KI tatsächlich semantisch analysieren Verified the AI analysis end-to-end with a real provider and fixed two gaps found during the live run. Findings & fixes: - gpt-5 series (Replit AI Integrations modelfarm default) rejected the hardcoded `temperature: 0.1` with HTTP 400, silently disabling AI analysis. Removed the temperature param from the OpenAI-compatible request for broad model compatibility (aiAnalysis.ts). - Per-rule AI config (enable/disable/severity) was only a global on/off gate and AI findings weren't mapped to the AI rule IDs, so individual rule severity was ignored. runAiAnalysis now receives the enabled AI rules, instructs the model to classify each finding into one of those ruleIds, drops findings for disabled rules, and overrides severity/axis with the configured values (aiAnalysis.ts + scanEngine.ts). End-to-end verification (Replit OpenAI integration, gpt-5-mini provider): - "KI-Analyse aktivieren" produces AI findings mapped to AI-PROMPT-INJECTION, AI-MALICIOUS-INTENT, AI-DATA-PRIVACY. - Disabling AI-MALICIOUS-INTENT removed its finding; setting AI-PROMPT-INJECTION to critical was reflected in the result. - Wrong baseUrl and invalid token (real OpenAI endpoint) produce understandable aiError messages with no token leak. Side effects / notes: - Set up the Replit OpenAI AI Integration (env vars) and created one enabled provider row ("Replit OpenAI") so AI analysis works out of the box. Each AI-enabled scan bills the user's Replit credits. - Test scans created during verification were deleted. - artifacts/api-server typecheck passes. Replit-Task-Id: 7321caa4-5079-4db7-8ed2-4ccaa74fa577 2026-06-10 13:56:15 +00:00			- [OpenAI gpt-5 temperature](openai-temperature-gpt5.md) — gpt-5* reject `temperature != 1`; omit temperature in OpenAI-compatible clients or AI analysis silently fails.