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 field-service-foundation-setup-designer-getgit 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/field-service-foundation-setup-designer-get)<a href="https://agentmods.dev/skills/forcedotcom/sf-skills/field-service-foundation-setup-designer-get"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/field-service-foundation-setup-designer-get/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/field-service-foundation-setup-designer-get"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/field-service-foundation-setup-designer-get.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00068 | $0.01558 |
| Opus 5 | $0.00034 | $0.00779 |
| Sonnet 5 | $0.00014 | $0.00312 |
| Haiku 4.5 | $0.00007 | $0.00156 |
Grade A, and why
field-service-foundation-setup-designer-get 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 4d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Field Service Foundation Setup Designer
Design or refine Field Service foundation data — Work Types, Skills, Service Territories, Operating Hours, and other associated Field Service objects — through structured interviews. Starting from scratch or from existing recommendations.
This skill runs a design conversation — it does not call Salesforce APIs directly. It collects the design through a structured conversation, whether starting from scratch or working from existing data, and confirms the final design with the user. This skill covers two design workflows in sequence (or independently):
- Work Types & Skills — 6-question interview
- Service Territories & Operating Hours — 3-question interview
Entry point
- Starting from scratch → run the full interview phases below to build the design.
- Have existing data — this includes scraped/read source output, JSON or text provided by the user, or any other external source brought into context. Show a plain-English summary of the proposed configuration as a starting reference, then immediately ask: "Would you like to go through a guided design interview to refine this, or proceed directly with this configuration?" Wait for the answer before doing anything else.
- Ready to create → show a plain-English summary of the records to be created (not raw JSON or skill names), ask for explicit confirmation, then proceed only after the user confirms.
Never expose internal skill names, SOR IDs, or tool references to the user.
When to use
- Starting Field Service setup from scratch — no existing Work Types or Territories yet
- When initial recommendations need adjustment for either work types or territories (or both)
- To explore different granularity levels (Work Types) or territory models (Territories)
- When customer provides additional context about their business or coverage areas
- During discovery sessions to design or iterate on the foundation data model
Design principles
- Structured questions with consistent intent
- Questions based on Work Type Implementation Guide and Service Territory Design Guide
- Adapt examples to customer's business context
- Intent stays consistent, wording adapts intelligently
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.
- 4d ago Changed 3a19dc5ed96f
- 7d ago First seen · 136 lines · 68 tokens per session scan A 22d018b45f92
field-service-foundation-setup-designer-get is a skill published in the GitHub repository forcedotcom/sf-skills (987 stars, last pushed yesterday), licensed Apache-2.0. It adds 68 tokens to every session and 1,558 once invoked, about $0.0003 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 2026-09-05.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…