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Agent Skill · AI 工具

sf-ai-agentscript(sf ai Agent 脚本)

sf-ai-agentscript 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。

sf-ai-agentscript 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 92。

总安装 24,425周安装 1,007GitHub Stars 401下载 8,056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:sf-ai-agentscript(sf ai Agent 脚本)
来源仓库:https://github.com/jaganpro/sf-skills
仓库路径:skills/sf-ai-agentscript
安装命令:
npx skills add https://github.com/jaganpro/sf-skills --skill sf-ai-agentscript
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/jaganpro/sf-skills --skill sf-ai-agentscript

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合围绕仓库状态、代码变更或协作事项进行整理。可结合来源仓库、安装命令和原始 README 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。

sf-ai-agentscript 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/sf-ai-agentscript

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/jaganpro/sf-skills --skill sf-ai-agentscript;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

    它需要需要联网,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

sf-ai-agentscript 怎么安装?

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

sf-ai-agentscript 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。

sf-ai-agentscript 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

sf-ai-agentscript 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。

sf-ai-agentscript 用的人多吗?

公开数据是累计安装 24,425 次,近一周安装 1,007 次,下载 8,056 次,GitHub 401 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。

sf-ai-agentscript 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。
  • 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。
  • 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

  • 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AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
sf-ai-agentscript

sf ai Agent 脚本 · 本页

24,425401需要联网MIT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

SF-AI-AgentScript Skill

Agent Script is the code-first path for deterministic Agentforce agents. Use this skill when the user is authoring .agent files, building finite-state topic flows, or needs repeatable control over routing, variables, actions, and publish behavior.

Start with the shortest guide first: references/activation-checklist.md Migrating from the Builder UI? Use references/migration-guide.md

When This Skill Owns the Task

Use sf-ai-agentscript when the work involves:

  • creating or editing .agent files
  • deterministic topic routing, guards, and transitions
  • Agent Script CLI workflows (sf agent generate authoring-bundle, sf agent validate authoring-bundle, sf agent preview, sf agent publish authoring-bundle, sf agent activate)
  • slot filling, instruction resolution, post-action loops, or FSM design

Delegate elsewhere when the user is:

If the user is in Builder Script / Canvas view but the outcome is a .agent authoring bundle, keep the work in sf-ai-agentscript.


Right-Size Determinism

  • Determinism is a dial, not a destination.
  • Use Agent Script when “mostly right” is not acceptable: gates, mandatory sequencing, explicit state transitions, compliance, or drift control.
  • If a workflow is fully static and linear, use Flow or Apex instead of scripting the conversation.
  • Prefer a deterministic envelope: deterministic entry/gate → flexible middle → deterministic closeout.
  • More determinism is not automatically better. Start minimal, then harden only the parts that show routing drift, sequencing failures, or compliance risk.

Required Context to Gather First

Ask for or infer:

  • agent purpose and whether Agent Script is truly the right fit
  • Service Agent vs Employee Agent
  • target org and publish intent
  • expected actions / targets (Flow, Apex, PromptTemplate, etc.)
  • whether the request is authoring, validation, preview, or publish troubleshooting

Activation Checklist

Before you author or fix any .agent file, verify these first:

  1. Exactly one start_agent block
  2. No mixed tabs and spaces
  3. Booleans are True / False
  4. No else if and no nested if
  5. No top-level actions: block
  6. No @inputs in set expressions
  7. linked variables have no defaults
  8. linked variables do not use object / list types
  9. Use explicit agent_type
  10. Use @actions. prefixes consistently
  11. Use run @actions.X only when X is a topic-level action definition with target:
  12. Do not branch directly on raw @system_variables.user_input contains/startswith/endswith for intent routing
  13. On prompt-template outputs, prefer is_displayable: False + is_used_by_planner: True
  14. Do not assume @outputs.X is scalar — inspect the output schema before branching or assignment

For the expanded version, use references/activation-checklist.md.


Non-Negotiable Rules

1) Service Agent vs Employee Agent

Agent typeRequiredForbidden / caution
AgentforceServiceAgentValid default_agent_user, correct permissions, target-org checks, prefer sf org create agent-userPublishing without a real Einstein Agent User
AgentforceEmployeeAgentExplicit agent_typeSupplying default_agent_user

Full details: references/agent-user-setup.md

2) Recommended top-level block convention

Use this order for consistency in this skill's examples and reviews:

config:
variables:
system:
connection:
knowledge:
language:
start_agent:
topic:

Official Salesforce materials present top-level blocks in differing sequences, and local validation evidence indicates multiple orderings compile. Treat this as a style convention, not a standalone correctness or publish blocker.

3) Critical config fields

FieldRule
developer_nameMust match folder / bundle name
descriptionPublic docs/examples should use this config field
agent_typeSet explicitly every time
default_agent_userService Agents only

Local tooling also accepts agent_description: for compatibility, but this skill's public docs and examples should prefer description:.

4) Syntax blockers you should treat as immediate failures

  • else if
  • nested if
  • comment-only if bodies
  • top-level actions:
  • invocation-level inputs: / outputs: blocks
  • reserved variable / field names like description and label

Canonical rule set: references/syntax-reference.md and references/validator-rule-catalog.md


Recommended Workflow

Recommended Authoring Workflow

Phase 1 — design the agent

  • decide whether the problem is actually deterministic enough for Agent Script
  • model topics as states and transitions as edges
  • define only the variables you truly need

Phase 2 — author the .agent

  • create config, system, start_agent, and topics first
  • add target-backed actions with full inputs: and outputs:
  • use available when for deterministic tool visibility
  • normalize raw intent/validation signals into booleans or enums before branching; avoid direct substring checks on raw user utterances for critical control flow
  • keep post-action checks at the top of instructions: ->

Default authoring stance

  • Default to direct .agent authoring and edits in source control.
  • Use sf agent generate authoring-bundle --no-spec only when the user wants local bundle scaffolding.
  • Treat sf agent generate agent-spec as optional ideation / topic bootstrap, not the default workflow.
  • Do not route Agent Script users toward sf agent create or sf agent generate template.

Phase 3 — validate continuously

Validation already runs automatically on write/edit. Use the CLI before publish:

sf agent validate authoring-bundle --api-name MyAgent -o TARGET_ORG --json

The validator covers structure, runtime gotchas, target readiness, and org-aware Service Agent checks. Rule IDs live in references/validator-rule-catalog.md.

Phase 4 — preview smoke test

Use the preview loop before publish:

  • derive 3–5 smoke utterances
  • start preview with the start / send / end subcommands, not bare sf agent preview
  • if you use --authoring-bundle, always choose a mode explicitly: --simulate-actions or --use-live-actions
  • inspect topic routing / action invocation / safety / grounding
  • fix and rerun up to 3 times

Full loop: references/preview-test-loop.md

Phase 5 — publish and activate

sf agent publish authoring-bundle --api-name MyAgent -o TARGET_ORG --json

# Manual activation
sf agent activate --api-name MyAgent -o TARGET_ORG

# CI / deterministic activation of a known BotVersion
sf agent activate --api-name MyAgent --version <n> -o TARGET_ORG --json

Publishing does not activate the agent. For automation, prefer --version <n> --json so activation is deterministic and machine-readable.


Deterministic Building Blocks

These execute as code, not suggestions:

  • conditionals
  • available when guards
  • variable checks
  • direct set / transition to
  • run @actions.X only when X is a topic-level action definition with target:
  • variable injection into LLM-facing text

Important distinction:

  • Deterministic: set, transition to, and run @actions.X for a target-backed topic action
  • LLM-directed: reasoning.actions: utilities / delegations such as @utils.setVariables, @utils.transition, and {!@actions.X} instruction references

If you need deterministic behavior for something that is currently modeled as a reasoning-level utility, either:

  • rewrite it as direct set / transition to, or
  • promote it to a topic-level target-backed action and run that action

See references/instruction-resolution.md and references/architecture-patterns.md.


Cross-Skill Integration

Cross-Skill Orchestration

TaskDelegate toWhy
Build flow:// targetssf-flowFlow creation / validation
Build Apex action targetssf-apex@InvocableMethod and business logic
Test topic routing / actionssf-ai-agentforce-testingFormal test specs and fix loops
Deploy / publishsf-deployDeployment orchestration

High-Signal Failure Patterns

SymptomLikely causeRead next
Internal Error during publishinvalid Service Agent user or missing action I/Oreferences/agent-user-setup.md, references/actions-reference.md
invalid input/output parameters on prompt template actionTarget template is in Draft status — activate it firstreferences/action-prompt-templates.md
Parser rejects conditionalselse if, nested if, empty if bodyreferences/syntax-reference.md
Action target issuesmissing Flow / Apex target, inactive Flow, bad schemasreferences/actions-reference.md
Prompt template runs but user sees blank responseprompt output marked is_displayable: Truereferences/production-gotchas.md, references/action-prompt-templates.md
Prompt action runs but planner behaves like output is missingoutput hidden from direct display but not planner-visiblereferences/production-gotchas.md, references/actions-reference.md
ACTION_NOT_IN_SCOPE on run @actions.Xrun points at a utility / delegation / unresolved action instead of a topic-level target-backed definitionreferences/syntax-reference.md, references/instruction-resolution.md
Deterministic cancel / revise / URL checks behave inconsistentlyraw @system_variables.user_input matching or string-method guards are being used as control-flow-critical validationreferences/syntax-reference.md, references/production-gotchas.md
@outputs.X comparisons or assignments behave unexpectedlythe action output is structured/wrapped, not a plain scalarreferences/actions-reference.md, references/syntax-reference.md
Preview and runtime disagreelinked vars / context / known platform issuesreferences/known-issues.md
Validate passes but publish failsorg-specific user / permission / retrieve-back issuereferences/production-gotchas.md, references/cli-guide.md

Reference Map

Start here

Publish / runtime safety

Architecture / reasoning

Validation / testing / debugging

Examples / scaffolds

Project documentation


Score Guide

ScoreMeaning
90+Deploy with confidence
75–89Good, review warnings
60–74Needs focused revision
< 60Block publish

Full rubric: references/scoring-rubric.md


Official Resources

平台分布

Cursor

29.02%
按下载量换算2,338

Claude Code

22.09%
按下载量换算1,780

Codex

17.9%
按下载量换算1,442

Antigravity

13.27%
按下载量换算1,069

Gemini CLI

8.44%
按下载量换算680

windsurf

3.12%
按下载量换算251

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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