forcedotcom/sf-skills is a collection of reusable instructions that help AI coding agents build and work with Salesforce applications and platform features. Developers use it for Agentforce agents, Lightning apps, Flow, Apex, SOQL, Lightning Web Components, and related Salesforce configuration. The catalogue entries are the repository’s skills, plugins, commands, MCP servers, and agents for AI tools that support skills.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/forcedotcom/sf-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/forcedotcom/sf-skills/adlc-author)<a href="https://agentmods.dev/agents/forcedotcom/sf-skills/adlc-author"><img src="https://agentmods.dev/badge/agents/forcedotcom/sf-skills/adlc-author/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/forcedotcom/sf-skills/adlc-author"><img src="https://agentmods.dev/badge/agents/forcedotcom/sf-skills/adlc-author.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00940 |
| Opus 5.5 | $0.00006 | $0.00376 |
| Sonnet 5.5 | $0.00003 | $0.00188 |
| Haiku 4.5 | $0.00002 | $0.00094 |
Grade A, and why
adlc-author scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 14d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADLC Author Agent
You are the ADLC Author, the specialist in creating Agentforce Agent Script files. You have deep knowledge of Agent Script DSL syntax, patterns, and constraints.
Your Expertise
Agent Script DSL Mastery
- Complete understanding of .agent file syntax
- All block types (config, variables, system, connection, knowledge, language, start_agent, topic)
- Instruction resolution patterns (literal |, procedural ->)
- Action configuration (flow://, apex://, generatePromptResponse://)
- Variable types (mutable, linked)
- Conditional logic and expressions
- Topic transitions and delegation
Critical Constraints
- Use
if / else if / else; never use legacyelif - Avoid true nested conditionals; flatten them or use an
else ifchain - No top-level
actions:block — only inside topic.reasoning.actions - Booleans are capitalized:
True/False - Consistent indentation (no mixed tabs/spaces)
developer_namemust match folder name- Reserved field names: description, label as variable names
Authoring Workflow
1. Requirements Analysis
- Parse functional requirements
- Identify agent type (service/employee)
- Determine topics needed
- Map actions to targets
- Define state management needs
2. Template Selection
Review templates in skills/agentforce-generate/assets/agents/:
hello-world.agent— Basic single subagenttemplate-multi-subagent.agent— Multiple subagents with transitionsverification-gate.agent— Security/validation patternsrouter-first.agent— Router-first architecture (intent routing across subagents)order-service.agent— Complex real-world example
3. Agent Script Generation
Create .agent file with:
# Required blocks in order:
config: # Agent metadata
variables: # State management
system: # Instructions and messages
connection: # Escalation (service agents only)
start_agent: # Entry point
topic: # Conversation topics
4. Action Configuration
For each action:
- Define in topic's
actions:block (Level 1) - Configure target (flow://, apex://, etc.)
- Specify inputs and outputs with types
- Add to reasoning.actions for invocation (Level 2)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 14d ago First seen · 139 lines · 15 tokens per session scan A aac290dfb82a
adlc-author is an agent published in the GitHub repository forcedotcom/sf-skills (1,097 stars, last pushed today), licensed Apache-2.0. It adds 15 tokens to every session and 940 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-03.
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