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 Jaganpro/sf-skills --skill sf-deploygit clone --depth 1 https://github.com/Jaganpro/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/jaganpro/sf-skills/sf-deploy)<a href="https://agentmods.dev/skills/jaganpro/sf-skills/sf-deploy"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-deploy/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/jaganpro/sf-skills/sf-deploy"><img src="https://agentmods.dev/badge/skills/jaganpro/sf-skills/sf-deploy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00090 | $0.01933 |
| Opus 5 | $0.00045 | $0.00966 |
| Sonnet 5 | $0.00018 | $0.00387 |
| Haiku 4.5 | $0.00009 | $0.00193 |
Grade A, and why
sf-deploy 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 9d 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 — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sf-deploy: Comprehensive Salesforce DevOps Automation
Use this skill when the user needs deployment orchestration: dry-run validation, targeted or manifest-based deploys, CI/CD workflow advice, scratch-org management, failure triage, or safe rollout sequencing for Salesforce metadata.
When This Skill Owns the Task
Use sf-deploy when the work involves:
sf project deploy start,quick,report, or retrieval workflows- release sequencing across objects, permission sets, Apex, and Flows
- CI/CD gates, test-level selection, or deployment reports
- troubleshooting deployment failures and dependency ordering
Delegate elsewhere when the user is:
- authoring Apex or LWC code → sf-apex, sf-lwc
- creating metadata definitions → sf-metadata
- building Flows → sf-flow
- doing org data operations → sf-data
- authoring Agent Script logic → sf-ai-agentscript
Critical Operating Rules
- Use
sfCLI v2 only. - On non-source-tracking orgs, deploy/retrieve commands require an explicit scope such as
--source-dir,--metadata, or--manifest. - Prefer
--dry-runfirst before real deploys. - For Flows, deploy safely and activate only after validation.
- Keep test-data creation guidance delegated to
sf-dataafter metadata is validated or deployed.
Default deployment order
| Phase | Metadata |
|---|---|
| 1 | Custom objects / fields |
| 2 | Permission sets |
| 3 | Apex |
| 4 | Flows as Draft |
| 5 | Flow activation / post-verify |
This ordering prevents many dependency and FLS failures.
Required Context to Gather First
Ask for or infer:
- target org alias and environment type
- deployment scope: source-dir, metadata list, or manifest
- whether this is validate-only, deploy, quick deploy, retrieve, or CI/CD guidance
- required test level and rollback expectations
- whether special metadata types are involved (Flow, permission sets, agents, packages)
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.
- assets/destructiveChanges.xml 3.4 KB
- assets/package.xml 2.4 KB
- CREDITS.md 4.8 KB
- LICENSE 1.1 KB
- README.md 3.3 KB
- references/agent-deployment-guide.md 20 KB
- references/deploy.sh 2.9 KB runs code
- references/deployment-report-template.md 1.8 KB
- references/deployment-workflows.md 8.8 KB
- references/orchestration.md 9.4 KB
- references/trigger-deployment-safety.md 11 KB
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.
- 9d ago First seen · 216 lines · 90 tokens per session scan A 2fb7b0b90ba5
sf-deploy is a skill published in the GitHub repository Jaganpro/sf-skills (423 stars, last pushed 4mo ago), licensed MIT. It adds 90 tokens to every session and 1,933 once invoked, about $0.0005 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 2026-08-30.
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