A planning workflow for Salesforce development, where Salesforce is a cloud platform for building business applications. It creates structured plans for Apex code, LWC components, Flow automation, integrations, and metadata deployments.

Use it to plan Apex features, user-interface components, automated business processes, integrations, or multi-step Salesforce builds.

It turns a broad Salesforce feature request into an organized implementation plan, making the work easier to understand and carry out.

sf-plan — Skill for Claude Code by divingsbysangam

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.

Any agent

npx skills add divingsbysangam/salesforce-compound-engineering-plugin --skill sf-plan

Clone the repo

git clone --depth 1 https://github.com/divingsbysangam/salesforce-compound-engineering-plugin

Made for: Claude Code.

Or install sf-compound-engineering, the plugin that ships this one along with the rest of its 68 skills, 1 hook, 2 MCP servers.

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/skills/divingsbysangam/salesforce-compound-engineering-plugin/sf-plan.svg)](https://agentmods.dev/skills/divingsbysangam/salesforce-compound-engineering-plugin/sf-plan)

Your own site

<a href="https://agentmods.dev/skills/divingsbysangam/salesforce-compound-engineering-plugin/sf-plan"><img src="https://agentmods.dev/badge/skills/divingsbysangam/salesforce-compound-engineering-plugin/sf-plan.svg" alt="Measured on agentmods" height="20"></a>

Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 858 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. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Excessive Agency · line 38
Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.

How audits are shown

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	$0.00110	$0.00858
Opus 5	$0.00055	$0.00429
Sonnet 5	$0.00022	$0.00172
Haiku 4.5	$0.00011	$0.00086

Measured 8d ago against content hash aa11c73b9758, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

sf-plan 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 8d 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.

skills/sf-plan/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/sf-plan

Persona dispatch. This skill dispatches its research personas as isolated subagents — see the dispatching-parallel-personas skill for the mechanics (isolated subagents, same-response parallelism, same-file-conflict check). This skill owns the research personas under references/personas/.

Principles enforced: 2 (verifiability), 4 (spec is the artifact), 7 (institutional knowledge). See PRINCIPLES.md.

Strategy grounding: If a STRATEGY.md exists at the repo root, read it first so the plan's tracks and metrics align with the program's stated approach.

Required reads

Procedure lives in sibling files, not only in this orchestrator:

Step 0: Check for Brainstorm — read references/step-0-check-for-brainstorm.md before acting on this section.
Step 1: Parallel Research (dispatch simultaneously) — read references/step-1-parallel-research-dispatch-simultaneously.md before acting on this section.
Step 2: Consolidate Research — read references/step-2-consolidate-research.md before acting on this section.
Step 3: Internal-First Discovery — read references/step-3-internal-first-discovery.md before acting on this section.
Step 4: Spec Flow Analysis — read references/step-4-spec-flow-analysis.md before acting on this section.
Critical Constraint — read references/critical-constraint.md before acting on this section.
Available Resources — read references/available-resources.md before acting on this section.
Output — read references/output.md before acting on this section.
After Planning — read references/after-planning.md before acting on this section.

Copy-paste-to-agent

Plan a Salesforce feature without writing code. Produce three artifacts: spec.md (business
requirements + acceptance criteria), plan.md (architecture + governor/sharing/security analysis),
and tasks.md (ordered implementation checklist). Before writing the plan, dispatch
sf-learnings-researcher, sf-repo-research-analyst, sf-best-practices-researcher, and
sf-framework-docs-researcher in parallel. The plan MUST include a "Verification Strategy"
section that names the test, assertion, or dry-run that proves the feature works — no
verification, no plan. Save under docs/plans/YYYY-MM-DD-<type>-<slug>-plan.md.

Read the full file on GitHub · 59 lines

Files

What ships with it

17 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

8d ago First seen · 59 lines · 110 tokens per session scan A aa11c73b9758

Subscribe to this mod's changes

sf-plan is a skill published in the GitHub repository divingsbysangam/salesforce-compound-engineering-plugin (10 stars, last pushed 4d ago), licensed MIT. It adds 110 tokens to every session and 858 once invoked, about $0.0006 per session on Opus 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 2026-08-31.

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