القائمة
Launch energy recovery worker subagents to populate selfEnergy data files. Use when the user asks to generate, update, or review self-energy recovery data for the ER calculator.
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
Reference and verification tools for the Genshin Impact damage calculator. TRIGGER when: verifying or looking up character/weapon/artifact game data (talent values, buff percentages, multipliers, conditions), reviewing or writing buff/formula implementations, or needing damage calc code patterns. Key tool: `impl_audit.py show C|W|A <id>` exports official game text and talent parameters — use this as the first step to verify in-game values.
Pull and triage GenshinTools user feedback from the production Cloudflare D1 feedback table. TRIGGER when the user asks to fetch, pull, review, summarize, or triage newest feedback, feedback since last time, feedback deltas, feedback-reports, or "what users said / what to build next". Uses the repo's incremental `npm run feedback:fetch` flow and summarizes only newly fetched submissions.
Draft and publish player-facing "What's New" / update log entries for GenshinTools. TRIGGER when the user asks to write, update, draft, or publish the update log / changelog / "what's new" / 更新日志. Gathers commits since the last published entry, summarizes only user-facing changes (no infra/refactors, no engineering tone), proposes bilingual zh+en entries for approval, then writes them to src/presets/updatelog/{en,zh}.md under the current date. Do NOT auto-run on commit or on a schedule — this is an on-demand, approval-gated flow.
UI design decision guide for GenshinTools. Use only for open-ended frontend design work: new surfaces, substantial redesigns, or unclear UX/layout choices where the agent must choose the structure. Do not use for direct user instructions, bug fixes, copy tweaks, mechanical UI changes, or routine edits where nearby code already shows the pattern.
Launch damage calculator worker subagents (review, triage, implement, excel, cleanup). Use when the user asks to review, audit, triage, implement, cross-validate, or clean up damage formulas or buff implementations.
Launch worker subagents that read gcsim character source code and extract v2-schema particle data. Use when the user asks to populate, update, or audit particle data from gcsim for the ER calculator.
| name | energy-agents |
| description | Launch energy recovery worker subagents to populate selfEnergy data files. Use when the user asks to generate, update, or review self-energy recovery data for the ER calculator. |
Launch specialized worker subagents to populate src/data/ercalc/selfEnergy/<region>.json with per-character energy recovery effects. Each worker reads character kits via impl_audit.py and writes to its own region file.
Note: This skill is specifically for the energy recovery data pipeline. For other ER calculator work, use standard subagents.
Each region has its own file under src/data/ercalc/selfEnergy/:
| File | Region |
|---|---|
mondstadt.json | Mondstadt |
liyue.json | Liyue |
inazuma.json | Inazuma |
sumeru.json | Sumeru |
fontaine.json | Fontaine |
natlan.json | Natlan |
nod-krai.json | Nod-Krai |
snezhnaya.json | Snezhnaya |
none.json | Travelers |
Before launching agents, run the candidate finder:
uv run --project scripts/pyproject.toml scripts/gen_self_energy.py
Use Codex's worker subagent type for every launch below. Tell each worker that it is not alone in the codebase, must not revert edits made by others, and must adapt to concurrent changes. The prompt body should be the matching launch block below, with the requested scope filled in.
Reads each candidate's full kit, determines energy recovery mechanics, and writes correct JSON entries to the region file.
Launch (region scope):
Read `.agents/agents/energy-review.md` and follow its instructions. Region: mondstadt
Launch (entity scope):
Read `.agents/agents/energy-review.md` and follow its instructions. Entities: raiden_shogun, dori
Typical full sweep: 7-8 agents in parallel.
All region agents are fully independent — each writes to its own file. Launch all in parallel.
gen_self_energy.py to get candidates