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implimpl 搜索

Agent Skill

impl 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。

总安装

376

周安装

16

GitHub Stars

2

下载量

132
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:impl(impl 搜索)
来源仓库:https://github.com/tercel/code-forge
仓库路径:skills/impl
安装命令:
npx skills add https://github.com/tercel/code-forge --skill impl
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/tercel/code-forge --skill impl

简介

用于查找、检索和筛选相关信息。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 通过 npx 安装,需结合原始 README 核验具体用法。
  • 安装前建议确认权限范围、维护状态及是否触发联网或文件操作。
  • impl 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Code Forge — Impl

Execute pending implementation tasks for a feature, following the plan generated by /code-forge:plan.

When to Use

  • Have a generated plan (state.json + tasks/ directory) ready for execution
  • Need to resume a partially completed feature
  • Need task-by-task execution with TDD and progress tracking

Examples

/code-forge:impl user-auth          # Execute tasks for user-auth feature
/code-forge:impl                    # Auto-detect pending feature

Workflow

Locate Feature → Confirm Execution → Task Loop (sub-agents) → Verify → Complete

Context Management

Step 3 dispatches a dedicated sub-agent for each task, so code changes from one task don't pollute the context of the next. The main context only handles coordination: reading state, dispatching sub-agents, and updating status.

Detailed Steps

@../shared/configuration.md


Step 0.5: Project Analysis

Before executing tasks, ensure the project context is understood:

@../shared/project-analysis.md

Execute PA.1 (Project Profile), PA.3 (Language-Specific Deep Scan for the feature's modules), and PA.5 (Existing Test Assessment). This context is passed to each task sub-agent so they:

  • Write tests using the CORRECT framework and patterns
  • Follow the project's ACTUAL architecture (not assumed patterns)
  • Handle language-specific constructs properly (Rust lifetimes, Go error chains, etc.)

Step 1: Locate Feature

1.1 With Feature Name Argument

If the user provided a feature name (e.g., /code-forge:impl user-auth):

  1. Look for {output_dir}/{feature_name}/state.json
  2. If not found, search {output_dir}/*/state.json for a feature whose feature field matches
  3. If not found in output_dir, also search .code-forge/tmp/{feature_name}/state.json and .code-forge/tmp/*/state.json (plan may have been created with --tmp)
  4. If still not found, show error: "Feature '{feature_name}' not found. Run /code-forge:status to see available features."

If found in .code-forge/tmp/, set output_dir to .code-forge/tmp/ and tmp_mode to true for the rest of the session.

1.2 Without Argument

If no feature name is provided:

  1. Scan both {output_dir}/*/state.json and .code-forge/tmp/*/state.json for all features
  2. Filter to features with status = "pending" or "in_progress" (exclude "completed")
  3. If none found: "No features ready for execution. Run /code-forge:plan to create one."
  4. If one found: use it automatically
  5. If multiple found: display table (mark tmp features with [tmp] suffix) and use AskUserQuestion to let user select

1.3 Validate Feature State

After locating the feature:

  1. Read state.json
  2. Check that tasks array is non-empty
  3. Check that task files in tasks/ directory exist
  4. Show feature progress summary: completed/in_progress/pending counts
  5. If all tasks are "completed": "All tasks already completed. Run /code-forge:review {feature} to review."

Step 2: Ask for Execution Method

Use AskUserQuestion:

  • "Start Execution Now (Recommended)" — execute tasks one by one, auto-track progress → enter Step 3
  • "Manual Execution Later" — save plan, show resume instructions (/code-forge:impl {feature})
  • "Team Collaboration Mode" — show guidelines: commit plan to Git, claim tasks via assignee, sync state.json
  • "View Plan Details" — display plan.md contents for review before executing

Step 3: Task Execution Loop (via Sub-agents)

Each task is executed by a dedicated sub-agent to prevent cross-task context accumulation. The main context only handles coordination: reading state, dispatching sub-agents, and updating status.

3.1 Coordination Loop (Main Context)

  1. Read state.json
  2. Find the next task in execution_order that is "pending" with no unmet dependencies
  3. If no such task exists: display "All tasks completed!" and exit loop
  4. Display: "Starting task: {id} - {title}"
  5. Update task status to "in_progress" in state.json
  6. Dispatch sub-agent for this task (see 3.2)
  7. Review the sub-agent's execution summary
  8. Ask user via AskUserQuestion: "Is the task completed?"

- "Completed, continue to next" → update status to "completed", continue loop - "Encountered issue, pause" → keep "in_progress", exit loop - "Skip this task" → update status to "skipped", continue loop

  1. Repeat from step 1

3.2 Task Execution Sub-agent

Spawn an Agent tool call with:

  • subagent_type: "general-purpose"
  • description: "Execute task: {task_id}"

Sub-agent prompt must include:

  • The task file path: {output_dir}/{feature_name}/tasks/{task_id}.md (sub-agent reads it)
  • The project root path
  • Tech stack and testing strategy (from state.json metadata or plan.md)
  • Instruction to follow TDD: write tests → run tests → implement → verify
  • Coding standards (mandatory): include the following standards in the sub-agent prompt so it writes quality code from the start:

@../shared/coding-standards.md

  • Instruction to return ONLY a concise execution summary

Sub-agent executes:

  1. Read the task file from disk
  2. Follow the task steps (TDD: write tests → run tests → implement → verify)
  3. Commit changes if all tests pass (with descriptive commit message)

Sub-agent must return a concise execution summary:

STATUS: completed | partial | blocked
FILES_CHANGED:
- path/to/file.ext (created | modified)
- ...
TEST_RESULTS: X passed, Y failed
SUMMARY: <1-2 sentence description of what was done>
ISSUES: <any blockers or concerns, or "none">

Main context retains: Only the execution summary (~0.5-1KB per task). All code changes, test outputs, and file reads stay in the sub-agent's context and are discarded.

3.3 Parallel Execution (Optional)

When multiple pending tasks have no mutual dependencies (none depends on another), they may be dispatched as parallel sub-agents using multiple Agent tool calls in a single message. Each sub-agent works in isolation on its own task.

Use parallel execution only when:

  • Tasks modify different files (no overlap in "Files Involved")
  • Tasks have no dependency relationship (neither depends on the other)
  • User has agreed to parallel execution

After all parallel sub-agents complete, review each summary and update state.json for all completed tasks before continuing the loop.

Step 4: Verify Generated Files

Before completion summary, verify all generated files:

Checks:

  1. Required files exist and are non-empty: overview.md, plan.md, state.json
  2. tasks/ directory exists and contains .md files with descriptive names
  3. state.json is valid JSON with required fields (feature, status, tasks, execution_order); task count matches task files; all IDs in execution_order match tasks entries
  4. plan.md contains: title heading, ## Goal, ## Task Breakdown, ## Acceptance Criteria
  5. overview.md contains ## Task Execution Order table

On pass: Show checklist with all items passing, continue.

On error (missing required files): Show what's missing. Attempt auto-fix:

  • Empty overview.md → generate template from plan data
  • Missing tasks/ → create directory
  • Missing state.json → generate initial state from task files found Then re-verify.

On warnings (count mismatch, missing optional section): Show warnings, continue by default.


Step 5: Completion Summary

After all tasks are completed:

  1. Update state.json with final status
  2. Regenerate the project-level overview ({output_dir}/overview.md)
Feature implementation completed!

Completed tasks: {completed}/{total}
Location: {output_dir}/{feature_name}/
Total time: {actual_time}

Next steps:
  /code-forge:review {feature_name}                        Review code quality
  /code-forge:verify                                       Verify all tests pass
  /code-forge:finish {feature_name}                        Merge / create PR

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.27%
按下载量换算51

Claude

29.17%
按下载量换算39

Cursor

17.88%
按下载量换算24

Gemini CLI

9.79%
按下载量换算13

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/tercel/code-forge --skill impl 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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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