菜单
Diagnose and improve Amy's Echo web sign-language ML detection quality. Use when working on MediaPipe landmarks, MLP inference thresholds, confidence/margin behavior, detector telemetry, fixture diagnostics, or profile-aware recognition regressions.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
Apply Amy's Echo Amy-first delivery workflow for implementation and review tasks. Use when changing code, tests, or docs in this repository. Enforce discovery, planning, Amy-impact validation, and mandatory verification before merge.
Execute Amy's Echo model training workflows end-to-end with reproducible evidence. Use when changing trainer code, training metadata contracts, model artifact handling, few-shot evaluation, or release-readiness checks for training outputs.
Build and harden Amy's Echo backend APIs using Express 5 and Zod contracts. Use when adding or modifying server routes, middleware, request validation, auth/profile checks, error handling, and response-shape guarantees.
Protect Amy's Echo account-versus-profile identity boundaries. Use when working on auth, settings, profile switching, uploads, training sync, or API flows where session/token and profileId can diverge.
Implement and debug MediaPipe Tasks Vision gesture recognition in Amy's Echo webapp. Use when changing webcam capture, landmark extraction, gesture recognizer setup, model loading, runtime confidence logic, or detection diagnostics tied to MediaPipe behavior.
Run Amy's Echo testing and quality gates with clear evidence reporting. Use when preparing a change for commit/PR, diagnosing regressions, or deciding the minimum safe check set for touched webapp, server, or integration areas.
| name | sign-language-ml-detection |
| description | Diagnose and improve Amy's Echo web sign-language ML detection quality. Use when working on MediaPipe landmarks, MLP inference thresholds, confidence/margin behavior, detector telemetry, fixture diagnostics, or profile-aware recognition regressions. |
Use this workflow for webapp gesture recognition and ML decision-path changes.
Prioritize these components:
webapp/src/gesture/core/, webapp/src/hooks/useSignLanguageDetector.tswebapp/src/gesture/installMlp.ts, webapp/src/gesture/modelClient.tswebapp/src/gesture/testing/fixtures/, npm --prefix webapp run diagnose:fixturesnpm --prefix webapp run diagnose:fixtures to generate comparison evidence.Use the checklist in references/detection-debug-checklist.md.
Always verify account/session and active profile context are both valid when detection depends on profile-trained labels.
Do not report success if:
Include:
references/detection-debug-checklist.mdreferences/detection-test-matrix.md