Token导航 LogoToken导航

Agent Skill · 开发

goals(goals 搜索)

goals 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

goals 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 3,829。

总安装 9,963周安装 407GitHub Stars 318下载 3,191核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:goals(goals 搜索)
来源仓库:https://github.com/boshu2/agentops
仓库路径:skills/goals
安装命令:
npx skills add https://github.com/boshu2/agentops --skill goals
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/boshu2/agentops --skill goals

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

goals 维护 GOALS.yaml 与 GOALS.md 健身规格,跟踪目标进展与回归检测。支持添加新目标、导出 JSON 快照与历史趋势分析,便于 CI 集成。提供漂移比较与元目标运行,防止指标膨胀与优先级漂移。建议与 /evolve 联动,确保每个迭代周期聚焦关键成果度量。

goals 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/goals

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/boshu2/agentops --skill goals;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

goals 怎么安装?

在终端执行 npx skills add https://github.com/boshu2/agentops --skill goals。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

goals 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

goals 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/boshu2/agentops --skill goals 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

goals 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

goals 用的人多吗?

公开数据是累计安装 9,963 次,近一周安装 407 次,下载 3,191 次,GitHub 318 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

goals 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
goals

goals 搜索 · 本页

9,963318执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

/goals — Fitness Goal Maintenance

Maintain GOALS.yaml and GOALS.md fitness specifications. Use ao goals CLI for all operations.

YOU MUST EXECUTE THIS WORKFLOW. Do not just describe it.

Quick Start

/goals                    # Measure fitness (default)
/goals init               # Bootstrap GOALS.md interactively
/goals steer              # Manage directives
/goals add                # Add a new goal
/goals drift              # Compare snapshots for regressions
/goals history            # Show measurement history
/goals export             # Export snapshot as JSON for CI
/goals meta               # Run meta-goals only
/goals validate           # Validate structure
/goals prune              # Remove stale gates
/goals migrate            # Migrate YAML to Markdown

Format Support

FormatFileVersionFeatures
YAMLGOALS.yaml1-3Goals with checks, weights, pillars
MarkdownGOALS.md4Goals + mission + north/anti stars + directives

When both files exist, GOALS.md takes precedence.

Mode Selection

Parse the user's input:

InputModeCLI Command
/goals, /goals measure, "goal status"measureao goals measure
/goals init, "bootstrap goals"initao goals init
/goals steer, "manage directives"steerao goals steer
/goals add, "add goal"addao goals add
/goals drift, "goal drift"driftao goals drift
/goals history, "goal history"historyao goals history
/goals export, "export goals"exportao goals export
/goals meta, "meta goals"metaao goals meta
/goals validate, "validate goals"validateao goals validate
/goals prune, "prune goals", "clean goals"pruneao goals prune
/goals migrate, "migrate goals"migrateao goals migrate

Measure Mode (default) — Observe

Step 1: Run Measurement

ao goals measure --json

Parse the JSON output. Extract per-goal pass/fail, overall fitness score.

Step 2: Directive Gap Assessment (GOALS.md only)

If the goals file is GOALS.md format:

ao goals measure --directives

For each directive, assess whether recent work has addressed it:

  • Check git log for commits mentioning the directive title
  • Check beads/issues related to the directive topic
  • Rate each directive: addressed / partially-addressed / gap

Step 3: Report

Present fitness dashboard:

Fitness: 5/7 passing (71%)

Gates:
  [PASS] build-passing (weight 8)
  [FAIL] test-passing (weight 7)
    └─ 3 test failures in pool_test.go

Directives:
  1. Expand Test Coverage — gap (no recent test additions)
  2. Reduce Complexity — partially-addressed (2 refactors this week)

Init Mode

ao goals init

Or with defaults:

ao goals init --non-interactive

Creates a new GOALS.md with mission, north/anti stars, first directive, and auto-detected gates. Error if file already exists.

Post-Init Enrichment

After ao goals init creates the scaffold, enrich it with product-aware content that the CLI cannot auto-detect:

Enrich North Stars with Outcomes

Review the generated north stars. If they are all feature-focused (e.g., "skills work across 4 runtimes"), nudge toward outcome-focused stars:

  • Feature-focused (weaker): "Skills work across 4 runtimes"
  • Outcome-focused (stronger): "A new user goes from install to first validated workflow in under 5 minutes"

Ask the user: "Your north stars describe features. What user outcome would tell you the product is actually working?" Add at least one outcome-focused star.

Enrich Anti-Stars from Failure Modes

Scan for proven failure patterns:

  1. Check .agents/retro/ — extract failure themes from retrospectives
  2. Check .agents/council/ or council index — look for FAIL verdicts and their root causes
  3. Check .agents/learnings/ — look for learnings tagged as anti-patterns

Convert the top 3 most common failure modes into anti-stars. Examples from real data:

  • "Product promises with no automated verification" (from council FAILs where claims had no gates)
  • "Goals that measure code metrics instead of user outcomes" (from retros where passing gates didn't improve product)
  • "Capture without compounding" (from flywheel analysis where knowledge was stored but never retrieved)

If no .agents/ data exists, use the defaults from ao goals init.

Add Product Directives

The CLI generates engineering-flavored directives (test coverage, complexity, lint). After init, also suggest product/growth directives by asking:

  1. "What's your biggest product gap right now?" → directive with steer: decrease
  2. "What user behavior do you want to increase?" → directive with steer: increase
  3. "What metric would tell you the product is working?" → directive with measurable target

Product directives sit alongside engineering ones in the same ## Directives section. See references/generation-heuristics.md for product directive patterns.

Add Product Gates

Check what product infrastructure exists and suggest appropriate gates:

InfrastructureSuggested Gate
.agents/learnings/ existsflywheel-compounding — knowledge above escape velocity
skills/quickstart/ existsquickstart-under-5min — onboarding time gate
docs/comparisons/ existscompetitive-freshness — comparison docs updated within 45 days
PRODUCT.md existsproduct-gaps-tracked — Known Gaps section has entries
ao flywheel status worksflywheel-promotion-rate — learnings promoted above threshold

Only suggest gates for infrastructure that actually exists. Don't create gates for aspirational features.

Steer Mode — Orient/Decide

Step 1: Show Current State

Run measure mode first to show current fitness and directive status.

Step 2: Propose Adjustments

Based on measurement:

  • If a directive is fully addressed → suggest removing or replacing
  • If fitness is declining → suggest new gates
  • If idle rate is high → suggest new directives

Product-aware steering: Also check for product dimension gaps:

  • If all directives are engineering-flavored (test, lint, build, refactor) → suggest at least one product/growth directive
  • If no directive cites a specific metric → flag: "Vague directives are a smell. Can any of these reference a specific number?"
  • If .agents/retro/ has new failure patterns not represented in anti-stars → suggest adding them
  • If PRODUCT.md has Known Gaps not covered by any directive → suggest a directive to close the gap

Step 3: Execute Changes

Use CLI commands:

ao goals steer add "Title" --description="..." --steer=increase
ao goals steer remove 3
ao goals steer prioritize 2 1

Add Mode

Add a single goal to the goals file. Format-aware — writes to GOALS.yaml or GOALS.md depending on which format is detected.

ao goals add <id> <check-command> --weight=5 --description="..." --type=health
FlagDefaultDescription
--weight5Goal weight (1-10)
--description—Human-readable description
--type—Goal type (health, architecture, quality, meta)

Example:

ao goals add go-coverage-floor "bash scripts/check-coverage.sh" --weight=3 --description="Go test coverage above 60%"

Drift Mode

Compare the latest measurement snapshot against a previous one to detect regressions.

ao goals drift                    # Compare latest vs previous snapshot

Reports which goals improved, regressed, or stayed unchanged.

History Mode

Show measurement history over time for all goals or a specific goal.

ao goals history                        # All goals, all time
ao goals history --goal go-coverage     # Single goal
ao goals history --since 2026-02-01     # Since a specific date
ao goals history --goal go-coverage --since 2026-02-01  # Combined

Useful for spotting trends and identifying oscillating goals.

Export Mode

Export the latest fitness snapshot as JSON for CI consumption or external tooling.

ao goals export

Outputs the snapshot to stdout in the fitness snapshot schema (see references/goals-schema.md).

Meta Mode

Run only meta-goals (goals that validate the validation system itself). Useful for checking allowlist hygiene, skip-list freshness, and other self-referential checks.

ao goals meta --json

See references/goals-schema.md for the meta-goal pattern.

Validate Mode

ao goals validate --json

Reports: goal count, version, format, directive count, any structural errors or warnings.

Prune Mode

ao goals prune --dry-run    # List stale gates
ao goals prune              # Remove stale gates

Identifies gates whose check commands reference nonexistent paths. Removes them and re-renders the file.

Migrate Mode

Convert between goal file formats.

ao goals migrate --to-md      # Convert GOALS.yaml → GOALS.md
ao goals migrate               # Migrate GOALS.yaml to latest YAML version

The --to-md flag creates a GOALS.md with mission, north/anti stars sections, and converts existing goals into the Gates table format. The original YAML file is backed up.

Examples

Checking fitness and directive gaps

User says: /goals

What happens:

  1. Runs ao goals measure --json to get gate results
  2. If GOALS.md format, runs ao goals measure --directives to get directive list
  3. Assesses each directive against recent work
  4. Reports combined fitness + directive gap dashboard

Result: Dashboard showing gate pass rates and directive progress.

Bootstrapping goals for a new project

User says: /goals init

What happens:

  1. Runs ao goals init which prompts for mission, stars, directives, and auto-detects gates
  2. Creates GOALS.md in the project root

Result: New GOALS.md ready for /evolve consumption.

Adding a new goal after a post-mortem

User says: /goals add go-parser-fuzz "cd cli && go test -fuzz=../internal/goals/ -fuzztime=10s" --weight=3 --description="Markdown parser survives fuzz testing"

What happens:

  1. Runs ao goals add with the provided arguments
  2. Writes the new goal in the correct format (YAML or Markdown)

Result: New goal added, measurable on next /goals run.

Troubleshooting

ProblemCauseSolution
"goals file already exists"Init called on existing projectUse /goals to measure, or delete file to re-init
"directives require GOALS.md format"Tried steer on YAML fileRun ao goals migrate --to-md first
No directives in measure outputGOALS.yaml doesn't support directivesMigrate to GOALS.md with ao goals migrate --to-md
Gates referencing deleted scriptsScripts were renamed or removedRun /goals prune to clean up
Drift shows no historyNo prior snapshots savedRun ao goals measure at least twice first
Export returns emptyNo snapshot file existsRun ao goals measure to create initial snapshot

See Also

  • /evolve — consumes goals for fitness-scored improvement loops
  • references/goals-schema.md — schema definition for both formats
  • references/generation-heuristics.md — goal quality criteria

Reference Documents

平台分布

Codex

37.46%
按下载量换算1,195

Claude

30.86%
按下载量换算985

Cursor

16.48%
按下载量换算526

Gemini CLI

10.02%
按下载量换算320

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/boshu2/agentops --skill goals 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills