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.
npx skills add forcedotcom/sf-skills --skill dx-org-analyzegit 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/skills/forcedotcom/sf-skills/dx-org-analyze)<a href="https://agentmods.dev/skills/forcedotcom/sf-skills/dx-org-analyze"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/dx-org-analyze/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/skills/forcedotcom/sf-skills/dx-org-analyze"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/dx-org-analyze.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 | $0.00223 | $0.02731 |
| Opus 5.5 | $0.00089 | $0.01092 |
| Sonnet 5.5 | $0.00045 | $0.00546 |
| Haiku 4.5 | $0.00022 | $0.00273 |
Grade A, and why
dx-org-analyze 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 28d 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tool Restrictions
Use ONLY the Bash tool to execute all sf CLI commands and Python scripts. Always include --json for sf commands. Do NOT use mcp__salesforce_dx__* tools.
Output artifacts for eval/testing: When an output directory is available, write results there. After executing the skill: (1) if the user specified an output path, write there immediately; (2) otherwise run [ -d force-app/main/adk-eval-output/ ] && echo 'force-app/main/adk-eval-output' to detect the eval directory; (3) write the full JSON result to <output-dir>/dx-org-analyze-result.json and the markdown report to <output-dir>/dx-org-analyze-result.md.
Data Access Hierarchy
When querying org data, always follow this priority order:
- SF CLI commands — Preferred. Use
sf org list metadata-types,sf org list metadata,sf org display,sf data query,sf limits api display, etc. - Direct REST/Tooling API calls — Last resort, only when SF CLI cannot provide the data.
Never bypass this hierarchy. If an SF CLI command exists for the operation, use it even if a direct API call would be simpler.
Authentication Rules
- All authentication MUST go through SF CLI (
sf org login web,sf org login jwt,sf org login access-token). - Never accept raw credentials (username + password), session IDs, or access tokens directly from the user.
- The collection script obtains its access token exclusively via
sf org display --json.
Workflow
Step 0: List Authenticated Orgs
Run this command to discover all authenticated orgs:
sf org list --json --skip-connection-status
Parse the JSON output. Collect orgs from all buckets (devHubs, nonScratchOrgs, scratchOrgs, sandboxes, other). Present authenticated orgs in a readable table:
| # | Alias | Username | Instance URL | Org ID | Type |
|---|
If fewer than 2 orgs are authenticated but at least 1 is available, offer the single-org introspect mode (see Introspect Workflow below). If no orgs are authenticated, STOP and advise:
You need at least 1 authenticated org. Run
sf org login web --alias <name>to authenticate.
What ships with it
11 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.
- README.md 13 KB
- references/collection-details.md 3.3 KB
- references/report-format.md 3.0 KB
- scripts/collect_org_data.py 36 KB runs code
- scripts/compute_diff.py 46 KB runs code
- scripts/introspect_org.py 16 KB runs code
- tests/fixtures/org_a.json 2.6 KB
- tests/fixtures/org_b.json 2.3 KB
- tests/README.md 1.8 KB
- tests/test_compute_diff.sh 10 KB runs code
- tests/test_consistency.sh 13 KB runs code
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.
- 28d ago Changed · -1 lines 18589b28df7d
- 1mo ago First seen · 262 lines · 223 tokens per session scan A 32424e702b0c
dx-org-analyze is a skill published in the GitHub repository forcedotcom/sf-skills (1,097 stars, last pushed today), licensed Apache-2.0. It adds 223 tokens to every session and 2,731 once invoked, about $0.0009 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 2026-09-16.
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