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。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/ranbot-ai/awesome-skills --skill goal-loop命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | goal-loop |
| description | Draft and explain persistent goal-loop prompts for long-running agent work with clear stop conditions. |
| category | Document Processing |
| source | antigravity |
| tags | ["markdown","api","claude","ai","agent","gpt","automation","workflow","template","design"] |
| url | https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/goal-loop |
/goal Loop/goal is/goal is a slash command that turns an agent prompt into a persistent agent looping plan → act → test → review → iterate until a stop condition is met, the user pauses, or the token budget runs out. Internally called the "Ralph loop."
Agents with the /goal feature right now: Codex, Claude Code, and Hermes Agent.
Key difference from a normal prompt: when a turn ends but the goal isn't met, the agent auto-continues instead of waiting for input.
Lifecycle states: pursuing, paused, achieved, unmet, budget-limited.
When monitoring a running /goal, every check should include a one-line update to the user: what the agent is doing and whether it is on track. Keep it extremely concise.
Not: a budget command, a safety boundary, "run forever", or a replacement for /plan. It's a contract enforcer with a verification loop.
/goal feature — right now: Codex, Claude Code, or Hermes AgentUse only when all three are true:
AGENTS.md present).Fits: migrations, coverage lifts, TDD feature builds, refactors with contract tests, prompt/eval optimization, deploy retry loops, bug-repro-then-fix.
Bad fits: exploratory work, vague "improve this", anything without a "done" definition, prod credentials, destructive shared-infra ops.
pytest -q, pnpm test, etc.)..md files or updating existing ones.Plus: tell the agent what to read first, ask it to work in checkpoints with a short progress log.
When the user wants a quick /goal instruction, produce a structured markdown block with one line per contract item (proper newlines, not flowing prose). Do not prefix the output with /goal — the user adds the slash command themselves in the composer. Emit only the contract body. Template:
**Objective:** <one-sentence objective>
**Read first:** <files/PLAN.md/issue>
**Constraints:** <what not to change, libs, conventions>
**Validate:** `<exact command>` after each change
**Document:** Write concise, targeted documentation for all changes — create new `.md` files or update existing docs as needed.
**Checkpoints:** work in checkpoints and log progress briefly
**Stop when:** <verifiable condition>, OR when further changes require human/product input
**Objective:** Migrate this project from Pydantic v1 to v2.
**Read first:** pyproject.toml, src/, tests/
**Constraints:** no public API changes; keep imports backwards-compatible via shims if needed; no new dependencies
**Validate:** `pytest -q` after each change
**Checkpoints:** work in checkpoints; log progress briefly
**Stop when:** full suite passes with zero deprecation warnings, OR when a change requires architecture decisions
**Objective:** Raise coverage in src/auth/ from ~38% to ≥75%.
**Read first:** src/auth/, tests/auth/, AGENTS.md
**Constraints:** no new deps; mirror existing test style; do not modify production code unless strictly required for testability
**Validate:** `pytest --cov=src/auth --cov-report=term-missing`
**Checkpoints:** work in checkpoints; log coverage delta each one
**Stop when:** coverage ≥75% AND all tests pass, OR when uncovered code needs design changes
/goal prompt must include a single sentence committing the agent to concise, targeted docs — new .md files or focused updates to existing docs.PLAN.md/GOAL_BRIEF.md) and make the goal point to it — keep the goal itself compact.Generate project-specific AGENTS.md and companion rules by analyzing a codebase. Supports full, minimal, update, and dry-run modes with package-manager detection, monorepos, backups, managed blocks, c
Run protected AAS maintainer sweeps, PR merge batches, canonical sync, Core preview checks, and scripted releases. Use for repository maintenance, main alignment, CLI/MCP/Workbench changes, or release
Provision backend infra through Cohesivity (cohesivity.ai): Postgres, hosting, auth, storage, and AI model APIs over one HTTP API. Use when a .cohesivity file exists or a project needs a backend.
基于 SOC 职业分类