What is build-agentforce-action?

A scaffold for a Salesforce Agentforce action, which is an operation an AI agent can invoke for a user or business process. It defines the action in Apex and connects it to an Agentforce topic and agent definition.

Use it to create an invocable Apex action, topic YAML, agent definition, test class, and starter evaluation. It supports read, write, composite, and external-callout action designs.

It makes the action’s purpose, data context, invoking person, and trust limits explicit before code is written. This helps keep AI-invoked operations constrained and testable.

build-agentforce-action — Command by BanibrataChatterjee

Install

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.

Clone the repo

git clone --depth 1 https://github.com/BanibrataChatterjee/AwesomeSalesforceSkills

Made for: Claude Code.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action/github.svg)](https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action)

Your own site

<a href="https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action/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.

Your own site · 80×15

<a href="https://agentmods.dev/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action"><img src="https://agentmods.dev/badge/commands/banibratachatterjee/awesomesalesforceskills/build-agentforce-action.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 575 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00000	$0.00575
Opus 5.5	$0.00000	$0.00230
Sonnet 5.5	$0.00000	$0.00115
Haiku 4.5	$0.00000	$0.00057

Measured 2mo ago against content hash 81068f249f2e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

build-agentforce-action 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 2mo 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.

commands/build-agentforce-action.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/build-agentforce-action — Scaffold a complete Agentforce action

Wraps agents/agentforce-builder/AGENT.md. Produces Apex @InvocableMethod + topic YAML + agent definition + test class + starter eval.

Step 1 — Collect inputs (ask all five upfront)

Ask:

1. Action name (user-facing label)?
   Example: "Summarize Account Cases"

2. Primary sObject the action grounds on?
   Example: Account

3. Actor invoking the action?
   Example: Service Agent / Sales Rep / Customer

4. Intent (what should the action do)?
   One or two sentences. What data does it retrieve / what does it change?

5. Trust constraints?
   Pick any that apply: no-pii-in-prompt, mask-email, no-external-callout,
   require-user-confirmation, audit-every-invocation, rate-limit-per-actor.
   Add free-form constraints as needed.

If any of the five is missing, STOP and ask.

Step 2 — Load the agent

Read agents/agentforce-builder/AGENT.md fully + the Agentforce skills + evals/framework.md + the templates under templates/agentforce/.

Step 3 — Execute

Follow the 6-step plan:

Classify the action (read-only / write / composite / callout)
Generate the Apex action class (subclass AgentActionSkeleton, CRUD/FLS via SecurityUtils, logging via ApplicationLogger)
Generate the topic YAML (classifier prompt, scope boundary, grounding sources, confirmation flag)
Generate the agent definition JSON
Generate the test class (including bulk + runAs + wrong-actor tests)
Generate the starter golden eval

Step 4 — Deliver

Action summary
Generated files, each as a fenced block labelled with its target path:
- Apex action class + meta
- Test class + meta
- Topic YAML
- Agent meta XML
- Golden eval markdown
Trust checklist (each constraint → where it's enforced)
Citations

/gen-tests if additional coverage beyond the scaffold is needed
/scan-security on the action Apex before promoting to production
Deploy the eval file under evals/golden/ and run evals/scripts/run_evals.py

Read the full file on GitHub · 80 lines

Changes

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.

2mo ago First seen · 80 lines · 0 tokens per session scan A 81068f249f2e

Subscribe to this mod's changes

build-agentforce-action is a command published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (4 stars, last pushed 6mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 575 tokens. 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 2026-08-31.

Backend and APIs Building agents

build-agentforce-action next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
build-agentforce-actionBanibrataChatterjee/AwesomeSalesforceSkills	Command	4	6mo ago	Apache-2.0	A	0	Claude Code
initfcakyon/claude-codex-settings	Command	1.2k	today	Apache-2.0	A	0	Claude Code
http-serviceMadAppGang/magus	Command	14	yesterday	MIT	A	27	Claude Code
buildAzure/ai-gateway	Command	5	10d ago	MIT	A	0	Claude Code
api-contract-reviewMozurok/fhorja.dev	Command	10	28d ago	MIT	A	64	Claude Code
start-10-1minicoohei/ai-agent-camp	Command	347	1mo ago	none	A	2	Claude Code
fastapimfmezger/ai_agent_dotfiles	Command	7	3mo ago	MIT	A	84	Claude Code, Gemini CLI