القائمة
Auto-discoverable wrapper for `.hforge/library/skills/javascript-engineering/SKILL.md`.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | javascript-engineering |
| description | Auto-discoverable wrapper for `.hforge/library/skills/javascript-engineering/SKILL.md`. |
| origin | Harness Forge |
.js, .jsx, .cjs, or .mjs files dominate the task.hforge/library/skills/javascript-engineering/SKILL.md.hforge/library/skills/javascript-engineering/references/.hforge/library/docs/authoring/enhanced-skill-import.md for import provenance and the added browser, bundler, and package-contract contextRESEARCH-SOURCES.md for the pack-level research summaryVALIDATION.md for the pack-level validation notes.hforge/library/rules/common/This wrapper is the discovery layer only. Load the canonical JavaScript skill
from .hforge/library/skills/javascript-engineering/ and use the provenance doc only when you
need maintainer-facing context behind the imported upgrades.
Auto-discoverable wrapper for `.hforge/library/skills/bug-investigation/SKILL.md`.
Auto-discoverable wrapper for `.hforge/library/skills/double-diamond-feature/SKILL.md`.
Use for defects, regressions, outages, flaky tests, and unexpected behavior. Guides the agent through triage, containment, reproduction, hypotheses, root-cause evidence, fix verification, and recurrence prevention. Do not use as the primary workflow for new features; use double-diamond-feature instead.
Use for meaningful feature development before coding. Guides the agent through Discover, Define, Develop, and Deliver with evidence, options, validation, and rollback notes. Do not use for bugs, regressions, outages, or flaky tests; use bug-investigation instead.
Auto-discoverable wrapper for `.hforge/library/skills/complex-task-protocol/SKILL.md`.
Automatic operating protocol for complex agent tasks. Use when work is multi-step, risky, cross-module, orchestration-heavy, or likely to benefit from bounded sidecar help, verification discipline, recovery checkpoints, and durable learning capture.