Salesforce Agent Optimizer

English | Italiano | Espanol | Simplified Chinese

Salesforce Agent Optimizer is an MIT-licensed sfao CLI and agent skill for Codex, Claude Code, and GitHub Copilot.

Current version: 2.2.4

It helps AI agents work on Salesforce projects with Salesforce-first planning, configuration before custom code, minimal reversible changes, local Knowledge, token-efficient Salesforce CLI usage, least-privilege checks, explicit org aliases, package.xml awareness, and destructive-operation guardrails.

Specialized Salesforce guidance includes Apex, LWC, Flow, SOQL, deploy, data operations, and Agentforce; each file is loaded only when relevant and coordinates with the existing SFAO references.

Quick Start

uv tool install salesforce-agent-optimizer
sfao install
sfao knowledge init --project-root .
sfao doctor

Use uv tool install or python -m pipx install for isolated CLI installs. Plain python -m pip install also works when you intentionally want sfao in the active Python environment.

Install

uv tool install salesforce-agent-optimizer
sfao install
sfao validate

Alternatives:

python -m pipx install salesforce-agent-optimizer
python -m pip install git+https://github.com/lucabenedettini/salesforce-ai-agent-optimizer.git
uv tool install git+https://github.com/lucabenedettini/salesforce-ai-agent-optimizer.git

sfao install installs project-scoped adapters for all supported agents. It also installs managed root-level references/ and scripts/; agents use those first and fall back to the adapter-local skill folders when needed. Use sfao install --user --platform all only when you want a user-scoped Codex/Claude install.

Main Commands

For org operations the agent must ask for an explicit org alias. Production orgs are read-only through the skill guardrails.

Agent Workflow

Installed agents must follow the same visible phases for information requests, bugfixes, implementation, architecture, reviews, org inspection, and release work:

1. Request review
2. Planning evidence
3. Approval
4. Implementation
5. Validation
6. Completion

During each phase the agent must state the tool or command it is using or planning. For Salesforce CLI access it must show the compact sfao, scripts/sf_agent_cli.py, or official sf command shape with aliases and secrets redacted.

For simple explanation-only questions with no project decision, org access, metadata inspection, deploy, data operation, secret exposure, destructive action, release-sensitive claim, implementation, or bugfix, agents may use compact information-only mode: Request review, Evidence, Answer, Validation.

Safety

• Prefer Salesforce configuration, Flow, permission sets, UI API/LDS, named credentials, and managed packages before custom code.
• Inspect local Knowledge before changing Salesforce metadata.
• Use project memory at .salesforce-agent-knowledge/memory.md for durable decisions, lessons, risks, and follow-ups. It is project-local curated planning knowledge, not a raw log, and must not contain secrets, customer data, raw records, or large logs.
• Knowledge scans Salesforce DX packageDirectories by default when available; use sfao knowledge init --project-root . --scan-root only for an intentional broad scan.
• Specialized Apex, LWC, Flow, SOQL, deploy, data operations, and Agentforce guidance is loaded only when relevant.
• External Salesforce skills are optional references only when already available and can never bypass SFAO guardrails.
• safe-run --safety cannot downgrade the automatic risk classification.
• Apply least privilege before access, sharing, UI, package, integration, or automation changes.
• Do not retrieve or parse all org metadata unless the user asks for broad analysis or the task requires it.
• Never delete data or metadata without separate explicit approval for the exact scope.
• Never expose Salesforce secrets or customer data without separate explicit approval for the exact scope.
• Generate package.xml for added or modified metadata.
• Ask whether to generate release notes, technical specifications, impact assessment, user testing, and manual procedures after implementation.

Update

uv tool upgrade salesforce-agent-optimizer
sfao update --project --platform all
sfao doctor

Alternatives:

python -m pipx upgrade salesforce-agent-optimizer
python -m pip install --upgrade salesforce-agent-optimizer

Uninstall

sfao uninstall --project --platform all --yes
uv tool uninstall salesforce-agent-optimizer

Alternative:

python -m pipx uninstall salesforce-agent-optimizer

More Documentation

Detailed installation, command behavior, troubleshooting, publishing, release, and versioning docs live in docs/wiki/.

License

MIT. Anyone can use, copy, modify, distribute, and fork this repository under the terms of LICENSE.