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Agent Skill · 研究检索

implement(实现)

implement 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

implement 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 49,058。

总安装 665周安装 34GitHub Stars 152下载 280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
MIT

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:implement(实现)
来源仓库:https://github.com/yonatangross/skillforge-claude-plugin
仓库路径:skills/implement
安装命令:
npx skills add https://github.com/yonatangross/skillforge-claude-plugin --skill implement
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/yonatangross/skillforge-claude-plugin --skill implement

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

implement 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于根据关键词、任务场景或来源线索进行信息搜集与整理的研究检索场景。通过 npx skills add 命令从 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态,注意是否触发联网、命令执行或文件读写操作。建议结合原始 README 和仓库内容进一步核验具体用法和功能边界。

来源仓库内路径:skills/implement

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/yonatangross/skillforge-claude-plugin --skill…;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

    它需要调用外部服务,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

implement 怎么安装?

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

implement 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。

implement 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

implement 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

implement 用的人多吗?

公开数据是累计安装 665 次,近一周安装 34 次,下载 280 次,GitHub 152 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。

implement 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
implement

实现 · 本页

665152调用外部服务MIT有提醒

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

Implement Feature

Parallel subagent execution for feature implementation with scope control and reflection.

Quick Start

/ork:implement user authentication
/ork:implement --model=opus real-time notifications
/ork:implement dashboard analytics

Argument Resolution

FEATURE_DESC = "$ARGUMENTS"  # Full argument string, e.g., "user authentication"
# $ARGUMENTS[0] is the first token, $ARGUMENTS[1] second, etc. (CC 2.1.59)

# Model override detection (CC 2.1.72)
MODEL_OVERRIDE = None
for token in "$ARGUMENTS".split():
    if token.startswith("--model="):
        MODEL_OVERRIDE = token.split("=", 1)[1]  # "opus", "sonnet", "haiku"
        FEATURE_DESC = FEATURE_DESC.replace(token, "").strip()

Pass MODEL_OVERRIDE to all Agent() calls via model=MODEL_OVERRIDE when set. Accepts symbolic names (opus, sonnet, haiku) or full IDs (claude-opus-4-6) per CC 2.1.74.


Step -1: MCP Probe + Resume Check

Run BEFORE any other step. Detect available MCP servers and check for resumable state.

# Probe MCPs (parallel — all in ONE message):
ToolSearch(query="select:mcp__memory__search_nodes")
ToolSearch(query="select:mcp__context7__resolve-library-id")

Write(".claude/chain/capabilities.json", JSON.stringify({
  "memory": <true if found>,
  "context7": <true if found>,
  "timestamp": now()
}))

# Resume check:
Read(".claude/chain/state.json")
# If exists and skill == "implement":
#   Read last handoff (e.g., 04-architecture.json)
#   Skip to current_phase
#   "Resuming from Phase {N} — architecture decided in previous session"
# If not: write initial state
Write(".claude/chain/state.json", JSON.stringify({
  "skill": "implement", "feature": FEATURE_DESC,
  "current_phase": 1, "completed_phases": [],
  "capabilities": capabilities
}))
Load: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/checkpoint-resume.md")

Step 0: Effort-Aware Phase Scaling (CC 2.1.76)

Read the /effort setting to scale implementation depth. The effort-aware context budgeting hook detects effort level automatically — adapt the phase plan accordingly:

Effort LevelPhases RunAgentsToken Budget
low1 (Discovery) → 5 (Implement) → 10 (Reflect)2 max~50K
medium1 → 2 → 5 → 7 (Scope Creep) → 103 max~150K
high (default)All 10 phases4-7~400K
Override: Explicit user selection in Step 0 (e.g., "Plan first" or "Worktree") overrides /effort downscaling. If user requests full exploration, respect that regardless of effort level.

Step 0a: Project Context Discovery

BEFORE any work, detect the project tier. This becomes the complexity ceiling for all patterns.

Scan codebase signals and classify into tiers 1-6 (Interview through Open Source). Each tier sets an architecture ceiling and determines which phases/agents to use.

Load tier details, workflow mapping, and orchestration mode: Read("${CLAUDE_SKILL_DIR}/references/tier-classification.md")

Worktree Isolation (CC 2.1.49)

For features touching 5+ files, offer worktree isolation to prevent conflicts with the main working tree:

AskUserQuestion(questions=[{
  "question": "Isolate this feature in a git worktree?",
  "header": "Isolation",
  "options": [
    {"label": "Yes — worktree (Recommended)", "description": "Creates isolated branch via EnterWorktree, merges back on completion", "markdown": "```\nWorktree Isolation\n──────────────────\nmain ─────────────────────────────▶\n  \\                              /\n   └─ feat-{slug} (worktree) ───┘\n      ├── Isolated directory\n      ├── Own branch + index\n      └── Auto-merge on completion\n\nSafe: main stays untouched until done\n```"},
    {"label": "No — work in-place", "description": "Edit files directly in current branch", "markdown": "```\nIn-Place Editing\n────────────────\nmain ──[edit]──[edit]──[edit]───▶\n       ▲       ▲       ▲\n       │       │       │\n     direct modifications\n\nFast: no branch overhead\nRisk: changes visible immediately\n```"},
    {"label": "Plan first", "description": "Research and design in plan mode before writing code", "markdown": "```\nPlan Mode Flow\n──────────────\n  1. EnterPlanMode($ARGUMENTS)\n  2. Read existing code\n  3. Research patterns\n  4. Design approach\n  5. ExitPlanMode → plan\n  6. User approves plan\n  7. Execute implementation\n\n  Best for: Large features,\n  unfamiliar codebases,\n  architectural decisions\n```"}
  ],
  "multiSelect": false
}])

If 'Plan first' selected:

# 1. Enter read-only plan mode
EnterPlanMode("Research and design: $ARGUMENTS")

# 2. Research phase — Read/Grep/Glob ONLY, no Write/Edit
#    - Read existing code in the target area
#    - Grep for related patterns, imports, dependencies
#    - Check tests, configs, and integration points
#    - If context7 available: query library docs

# 3. Design the plan — produce:
#    - File map: which files to create/modify
#    - Architecture decisions with rationale
#    - Task breakdown with acceptance criteria
#    - Risk assessment and edge cases

# 4. Exit plan mode — returns plan to user for approval
ExitPlanMode()

# 5. User reviews plan. If approved → continue to Phase 1 (Discovery)
#    with the plan as input. If rejected → revise or stop.

If worktree selected:

  1. Call EnterWorktree(name: "feat-{slug}") to create isolated branch
  2. All agents work in the worktree directory
  3. On completion, merge back: git checkout {original-branch} && git merge feat-{slug}
  4. If merge conflicts arise, present diff to user via AskUserQuestion

Load worktree details: Read("${CLAUDE_SKILL_DIR}/references/worktree-isolation-mode.md")


Task Management (MANDATORY)

BEFORE doing ANYTHING else, create tasks to track progress:

# 1. Create main task IMMEDIATELY
TaskCreate(
  subject="Implement: {feature}",
  description="Feature implementation with parallel subagents",
  activeForm="Implementing {feature}"
)

# 2. Create subtasks for each phase
TaskCreate(subject="Research best practices and docs", activeForm="Researching best practices")  # id=2
TaskCreate(subject="Micro-plan: scope, files, criteria", activeForm="Micro-planning")            # id=3
TaskCreate(subject="Architecture design (parallel agents)", activeForm="Designing architecture") # id=4
TaskCreate(subject="Implement and write tests", activeForm="Implementing code")                  # id=5
TaskCreate(subject="Integration verification", activeForm="Verifying integration")               # id=6
TaskCreate(subject="Scope creep check", activeForm="Checking scope creep")                       # id=7
TaskCreate(subject="E2E verification", activeForm="Running E2E verification")                    # id=8
TaskCreate(subject="Document and reflect", activeForm="Documenting decisions")                   # id=9

# 3. Set dependencies for sequential phases
TaskUpdate(taskId="3", addBlockedBy=["2"])  # Plan needs research
TaskUpdate(taskId="4", addBlockedBy=["3"])  # Architecture needs plan
TaskUpdate(taskId="5", addBlockedBy=["4"])  # Implementation needs architecture
TaskUpdate(taskId="6", addBlockedBy=["5"])  # Integration needs implementation
TaskUpdate(taskId="7", addBlockedBy=["6"])  # Scope creep needs integration
TaskUpdate(taskId="8", addBlockedBy=["7"])  # E2E needs scope check
TaskUpdate(taskId="9", addBlockedBy=["8"])  # Docs need E2E

# 4. Before starting each task, verify it's unblocked
task = TaskGet(taskId="2")  # Verify blockedBy is empty

# 5. Update status as you progress
TaskUpdate(taskId="2", status="in_progress")  # When starting
TaskUpdate(taskId="2", status="completed")    # When done — repeat for each subtask

Workflow (10 Phases)

PhaseActivitiesAgents
1. DiscoveryResearch best practices, Context7 docs, break into tasks—
2. Micro-PlanningDetailed plan per task (load ${CLAUDE_SKILL_DIR}/references/micro-planning-guide.md)—
3. WorktreeIsolate in git worktree for 5+ file features (load ${CLAUDE_SKILL_DIR}/references/worktree-workflow.md)—
4. Architecture4 parallel background agentsworkflow-architect, backend-system-architect, frontend-ui-developer, llm-integrator
5. Implementation + TestsParallel agents, single-pass artifacts with mandatory testsbackend-system-architect, frontend-ui-developer, llm-integrator, test-generator
6. Integration VerificationCode review + real-service integration testsbackend, frontend, code-quality-reviewer, security-auditor
7. Scope CreepCompare planned vs actual (load ${CLAUDE_SKILL_DIR}/references/scope-creep-detection.md)workflow-architect
8. E2E VerificationBrowser + API E2E testing (load ${CLAUDE_SKILL_DIR}/references/e2e-verification.md)—
9. DocumentationSave decisions to memory graph—
10. ReflectionLessons learned, estimation accuracyworkflow-architect

Load agent prompts: Read("${CLAUDE_SKILL_DIR}/references/agent-phases.md")

For Agent Teams mode: Read("${CLAUDE_SKILL_DIR}/references/agent-teams-phases.md")

Phase Handoffs (CC 2.1.71)

Write handoff JSON after major phases. See chain-patterns skill for schema.

After PhaseHandoff FileKey Outputs
1. Discovery01-discovery.jsonBest practices, library docs, task breakdown
2. Micro-Plan02-plan.jsonFile map, acceptance criteria per task
4. Architecture04-architecture.jsonDecisions, patterns chosen, agent results
5. Implementation05-implementation.jsonFiles created/modified, test results
7. Scope Creep07-scope.jsonPlanned vs actual, PR split recommendation

Progressive Output (CC 2.1.76)

Output results incrementally after each phase — don't batch everything until the end:

After PhaseShow User
1. DiscoveryKey findings, library recommendations, task breakdown
4. ArchitectureEach agent's design decisions as they return
5. ImplementationFiles created/modified per agent, test results
7. Scope CreepPlanned vs actual delta, PR split recommendation

When agents run with run_in_background=true, output each agent's findings as soon as it returns — don't wait for all agents to finish. This gives users ~60% faster perceived feedback and enables early intervention if an agent's approach diverges from the plan.

Worktree-Isolated Implementation (CC 2.1.50)

Phase 5 agents SHOULD use isolation: "worktree" to prevent file conflicts:

Agent(subagent_type="backend-system-architect",
  prompt="Implement backend: {feature}. Architecture: {from 04-architecture.json}",
  isolation="worktree", run_in_background=true)
Agent(subagent_type="frontend-ui-developer",
  prompt="Implement frontend: {feature}...",
  isolation="worktree", run_in_background=true)
Agent(subagent_type="test-generator",
  prompt="Generate tests: {feature}...",
  isolation="worktree", run_in_background=true)

Post-Deploy Monitoring (CC 2.1.71)

After final PR, schedule health monitoring:

# Guard: Skip cron in headless/CI (CLAUDE_CODE_DISABLE_CRON)
# if env CLAUDE_CODE_DISABLE_CRON is set, run a single check instead
CronCreate(
  schedule="0 */6 * * *",
  prompt="Health check for {feature} in PR #{pr}:
    gh pr checks {pr} --repo {repo}.
    If healthy 24h → CronDelete. If errors → alert."
)

context7 with Detection

if capabilities.context7:
  mcp__context7__resolve-library-id({ libraryName: "next-auth" })
  mcp__context7__query-docs({ libraryId: "...", query: "..." })
else:
  WebFetch("https://docs.example.com/api")  # T1 fallback

Issue Tracking

If working on a GitHub issue, run the Start Work ceremony from issue-progress-tracking and post progress comments after major phases.

Feedback Loop

Maintain checkpoints after each task. Load triggers: Read("${CLAUDE_SKILL_DIR}/references/feedback-loop.md")


Test Requirements Matrix

Phase 5 test-generator MUST produce tests matching the change type. Each change type maps to specific required tests and testing rules.

Load test matrix, real-service detection, and phase 9 gate: Read("${CLAUDE_SKILL_DIR}/references/test-requirements-matrix.md")


Key Principles

  • Tests are NOT optional — each task includes its tests, matched to change type (see matrix above)
  • Parallel when independent — use run_in_background: true, launch all agents in ONE message
  • Output limits (CC 2.1.77+): Opus 4.6 defaults to 64k output tokens (128k upper bound). Generate complete artifacts in a single pass when possible; chunk across turns if output exceeds the limit
  • Micro-plan before implementing — scope boundaries, file list, acceptance criteria
  • Detect scope creep (phase 7) — score 0-10, split PR if significant
  • Real services when available — if docker-compose/testcontainers exist, use them in Phase 6
  • Reflect and capture lessons (phase 10) — persist to memory graph
  • Clean up agents — use TeamDelete() after completion; press Ctrl+F twice as manual fallback. Note: /clear (CC 2.1.72+) preserves background agents
  • Exit worktrees — call ExitWorktree(action: "keep") in Phase 10 if worktree was entered in Step 0; never leave orphaned worktrees

Next Steps (suggest to user after implementation)

/ork:verify {FEATURE}              # Grade the implementation
/ork:cover {FEATURE}               # Generate test suite
/ork:commit                        # Commit changes
/loop 10m npm test                 # Watch tests while iterating
/loop 30m /ork:verify {FEATURE}    # Periodic quality gate

Agent Coordination

Context Passing

All spawned agents receive: changed files list, project tier, architectural constraints, and decisions from prior phases (discovery, plan). Pass via the agent prompt, not just "implement X".

SendMessage (Active Coordination)

When backend and frontend agents need to align on API contracts:

SendMessage(to="frontend-ui-developer", message="API endpoint is POST /api/auth with {token, refreshToken} response shape")
SendMessage(to="test-generator", message="Backend uses JWT — mock auth middleware in test fixtures")

Skill Chain

After implementation completes, chain to verification:

TaskCreate(subject="Verify implementation", activeForm="Verifying changes", addBlockedBy=[impl_task_id])
# Then: /ork:verify {feature}

Related Skills

  • ork:explore: Explore codebase before implementing
  • ork:verify: Verify implementations work correctly
  • ork:issue-progress-tracking: Auto-updates GitHub issues with commit progress

References

Load on demand with Read("${CLAUDE_SKILL_DIR}/references/<file>"):

FileContent
agent-phases.mdAgent prompts and spawn templates
agent-teams-phases.mdAgent Teams mode phases
interview-mode.mdInterview/take-home constraints
orchestration-modes.mdTask tool vs Agent Teams selection
feedback-loop.mdCheckpoint triggers and actions
cc-enhancements.mdCC version-specific features
agent-teams-full-stack.mdFull-stack pipeline for teams
team-worktree-setup.mdTeam worktree configuration
micro-planning-guide.mdDetailed micro-planning guide
scope-creep-detection.mdPlanned vs actual comparison
worktree-workflow.mdGit worktree workflow
e2e-verification.mdBrowser + API E2E testing guide
worktree-isolation-mode.mdWorktree isolation details
tier-classification.mdTier classification, workflow mapping, orchestration mode
test-requirements-matrix.mdTest matrix by change type, real-service detection, phase 9 gate

平台分布

Claude Code

27.09%
按下载量换算76

OpenCode

25.18%
按下载量换算71

Antigravity

20.83%
按下载量换算58

Gemini CLI

13.2%
按下载量换算37

windsurf

9.15%
按下载量换算26

trae

3.28%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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