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Agent Skill · 开发

prompt-template-wizard(提示模板向导)

用于辅助提示词、系统指令、Agent 行为约束和工作流模板的整理。它适合让 Agent 规范任务边界、统一输出格式、拆分操作步骤或优化提示词可复用性。使用时需要保留真实业务约束,不要把示例当硬规则;涉及自动执行、外部工具或高风险操作时,应在提示词中明确确认步骤、权限边界和失败处理方式。

prompt-template-wizard 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;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 16,500。

总安装 494周安装 21GitHub Stars 10下载 173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:prompt-template-wizard(提示模板向导)
来源仓库:https://github.com/jawwadfirdousi/agent-skills
仓库路径:skills/prompt-template-wizard
安装命令:
npx skills add https://github.com/jawwadfirdousi/agent-skills --skill prompt-template-wizard
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/jawwadfirdousi/agent-skills --skill prompt-template-wizard

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。

用于辅助提示词、系统指令和工作流模板的整理。适合规范任务边界或统一输出格式。prompt-template-wizard 属于开发类 Skill,可作为该场景下的辅助能力补充。使用时需要保留真实业务约束,不要把示例当硬规则。涉及高风险操作时应明确确认步骤和权限边界。

适用于 Codex、Claude、Cursor 和 Gemini CLI。

来源仓库内路径:skills/prompt-template-wizard

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/jawwadfirdousi/agent-skills --skill prompt-tem…;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

prompt-template-wizard 怎么安装?

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

prompt-template-wizard 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。

prompt-template-wizard 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

prompt-template-wizard 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。

prompt-template-wizard 用的人多吗?

公开数据是累计安装 494 次,近一周安装 21 次,下载 173 次,GitHub 10 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。

prompt-template-wizard 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 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
prompt-template-wizard

提示模板向导 · 本页

49410只读未明确通过

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

Prompt Template Wizard (Feature + Bug Fix)

Goal

Convert an incomplete request into a complete, low-ambiguity, paste-ready prompt template by:

  1. collecting missing fields via targeted questions,
  2. validating constraints and internal consistency,
  3. outputting a final prompt that is structured and scope-bounded.

This skill is interactive: keep asking questions until completion criteria are met.


Operating rules (strict)

  • Ask only for information that is missing, conflicting, or required by this spec.
  • Ask clarifying questions only if blocked, except the required testing question in this spec.
  • If something is ambiguous but not blocking, proceed with the simplest valid assumption and list it under “Assumptions”.
  • Do not expand scope. Implement exactly and only what the template needs.
  • Keep outputs compact and structured (section headers + bullets).
  • Questioning strategy: ask as many questions as needed in one message to eliminate ambiguity fast. If any remain unanswered, keep asking in subsequent turns until all required fields are filled and all conflicts resolved.
  • Localization: do not ask localization questions. Always apply the default localization policy.

The schema you must fill (TemplateSpec)

Maintain a working draft internally as a structured object with these fields.

A) Header

  • role
  • repo_app (optional identifier)
  • task_type ∈ {Feature, Bug fix, Refactor supporting bug fix} (must be exactly one)
  • output_rules[] (concise bullets)

B) Goal + context

  • goal_one_liner
  • background_bullets[] (2–6)
  • current_behavior
  • desired_behavior

C) Scope control

  • in_scope[] (>= 2)
  • out_of_scope[] (>= 1)

D) Definition of done

  • acceptance_criteria[] (observable, checkbox-ready)
  • nonfunctional:

- performance - security_privacy

  • telemetry_logging (optional)

E) Bug-only block (required if task_type = Bug fix)

  • repro_steps[]
  • actual
  • expected
  • frequency
  • impact
  • regression (yes/no/unknown + since when)

F) Codebase pointers (required)

  • relevant_paths[] (file paths)
  • related_ids[] (issues/PRs/links, may be empty if none)
  • tests_paths[] (test file paths, may be empty if unknown)

G) Testing (required, resolved; no option menus in final prompt)

  • automated_tests ∈ {Unit, Integration, UI, Snapshot, None}
  • testing_notes (optional)
  • manual_verification[] (required; at least 2 bullets)
  • tests_skip_risk_mitigation (required if automated_tests = None)

Important: During questioning, you may present choices. In the final prompt output, you must state the resolved decision as a declarative fact (no “choose one or more”).

H) Constraints

  • must_not_change[]
  • must_use[]
  • must_avoid[]

I) Localization (defaulted, always present)

  • localization_policy (default, required):

- “Use the localization system and patterns already implemented in the application. Do not introduce a new i18n approach. If no localization exists, add strings in the minimal way consistent with the codebase and keep future localization straightforward.”

J) Inputs

  • snippets_logs_payloads (free text; may be “none”)

Completion criteria (do not finalize until all pass)

A TemplateSpec is complete only if:

  1. No required field is empty (including codebase pointers and testing).
  2. task_type is exactly one of the allowed values (no hedging like “feature or bug”).
  3. No contradictions between goal, desired behavior, acceptance criteria, and scope.
  4. Acceptance criteria are testable/observable (avoid subjective language).
  5. Scope is bounded (>=2 in-scope, >=1 out-of-scope).
  6. If Bug fix: repro steps are runnable and expected/actual are concrete.
  7. Testing is explicit:

- automated_tests is set - manual_verification has >=2 bullets - if automated_tests = None, risk/mitigation is present

  1. Localization section is present with the default localization policy.
  2. Output rules include: plan-first, minimal diffs, testing adherence, assumptions list, ask-only-if-blocked.

Workflow

Step 1: Ingest

Map any user-provided content into TemplateSpec fields. Leave missing fields empty.

Step 2: Validate and generate questions

Create a “Missing/Conflicting” list and ask the questions needed to resolve it. Prioritize blockers in this order:

  1. task_type and goal_one_liner
  2. testing (mandatory: automated_tests + manual verification expectations)
  3. current vs desired behavior
  4. acceptance_criteria and definition-of-done thresholds
  5. scope (in/out)
  6. bug repro details (if bug fix)
  7. codebase pointers
  8. constraints

Question design:

  • Use multiple-choice for enums (task_type, automated_tests, regression, frequency).
  • Use checkbox-style prompts for scope and acceptance criteria.
  • Ask for a concrete manual verification checklist even if automated tests are “None”.

Step 3: Update draft

Update TemplateSpec with answers and re-run validation.

Step 4: Finalize output

When complete, output exactly 3 things:

  1. Final Prompt Template (paste-ready)
  2. TemplateSpec (filled)
  3. Consistency checklist (criteria 1–9)

Do not output the full prompt template before completion.


Output format requirements (while collecting info)

When you are still collecting info, output a single merged section:

OPEN ITEMS (missing, conflicting, and questions)

  • Start with up to 10 bullets summarizing what is missing or conflicting.
  • Immediately follow with the questions needed to resolve them.
  • Number questions consecutively (no fixed limit).
  • Each question must include:

- expected answer type (multiple-choice, short text, bullets, checkbox list) - brief example if useful

  • Continue asking across turns until all required fields are answered and conflicts resolved.

Important: Always include the testing questions until testing is fully resolved.


Output format requirements (final)

The Final Prompt Template must be one block the user can paste, using this structure:

ROLE OUTPUT RULES TASK TYPE GOAL CONTEXT SCOPE (IN / OUT) DEFINITION OF DONE BUG DETAILS (only if applicable) CODEBASE POINTERS TESTING CONSTRAINTS LOCALIZATION INPUTS REQUEST

Verbosity: compact bullets, no long narrative paragraphs.


Final Prompt Template (the target shape)

When the TemplateSpec is complete, emit the following template filled with the user’s content:

ROLE
You are <role> working in <repo_app if provided>. Implement exactly and only the scope below.

OUTPUT RULES
1) Plan first, then implement.
2) Keep diffs minimal and localized. Preserve existing patterns and style.
3) Tests: follow the TESTING section below exactly. Do not propose additional test types unless blocked by constraints.
4) Include an Assumptions section in the final response (only assumptions actually used).
5) Ask clarifying questions only if blocked.
6) Add intent comments using existing style where needed (REQUIREMENT:, UX:, BUGFIX:).

TASK TYPE
<Feature | Bug fix | Refactor supporting bug fix>  (exactly one)

GOAL
<goal_one_liner>

CONTEXT
- Background:
  - <background_bullets...>
- Current behavior:
  - <current_behavior>
- Desired behavior:
  - <desired_behavior>

SCOPE
IN
- <in_scope...>
OUT
- <out_of_scope...>

DEFINITION OF DONE
Acceptance criteria (observable)
- [ ] <acceptance_criteria...>

Non-functional requirements
- Performance: <performance>
- Security/privacy: <security_privacy>

Telemetry/logging (optional)
- <telemetry_logging or “none”>

BUG DETAILS (only if TASK TYPE = Bug fix)
REPRO STEPS
1) <repro_steps...>
ACTUAL
<actual>
EXPECTED
<expected>
FREQUENCY
<frequency>
IMPACT
<impact>
REGRESSION
<regression>

CODEBASE POINTERS
- Relevant files/modules: `<relevant_paths...>`
- Related issues/PRs: <related_ids or “none”>
- Tests to update: `<tests_paths...>` (or “unknown”)

TESTING
- Automated tests: <Unit | Integration | UI | Snapshot | None> (already decided).
- Notes/constraints: <testing_notes or “none”>
- Manual verification:
  - <manual_verification...>
- Risk/mitigation (required if Automated tests = None): <tests_skip_risk_mitigation>

CONSTRAINTS
Must not change
- <must_not_change...>

Must use
- <must_use...>

Must avoid
- <must_avoid...>

LOCALIZATION
- Policy: Use the localization system and patterns already implemented in the application. Do not introduce a new i18n approach. If no localization exists, add strings in the minimal way consistent with the codebase and keep future localization straightforward.

INPUTS
<snippets_logs_payloads>

REQUEST
Execute in this order:
1) Plan (3–8 bullets)
2) Tests (what you changed/added or why skipped; include test-impact note)
3) Verification checklist (manual + automated)
4) Assumptions

Apply scope discipline: implement exactly and only the IN scope.
Assumption policy: ask only if blocked.

平台分布

Codex

33.92%
按下载量换算59

Claude

29.35%
按下载量换算51

Cursor

17.44%
按下载量换算30

Gemini CLI

9.33%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

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