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-mobile-branding-configuregit 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-mobile-branding-configure)<a href="https://agentmods.dev/skills/forcedotcom/sf-skills/field-service-mobile-branding-configure"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/field-service-mobile-branding-configure/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-mobile-branding-configure"><img src="https://agentmods.dev/badge/skills/forcedotcom/sf-skills/field-service-mobile-branding-configure.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
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 12 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.
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 | $0.00135 | $0.02160 |
| Opus 5 | $0.00068 | $0.01080 |
| Sonnet 5 | $0.00027 | $0.00432 |
| Haiku 4.5 | $0.00014 | $0.00216 |
Grade A, and why
field-service-mobile-branding-configure 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 — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Field Service Mobile Branding
This skill ingests a brand source and produces a 14-field color scheme that gets applied to the org-default FieldServiceMobileSettings record (DeveloperName='Field_Service_Mobile_Settings', IsDefault=true). Confirmation with the user happens between derivation and apply — never apply without approval.
Source: This skill was authored by Chad Barbour and is mirrored from an upstream Field Service assets repository. Methodology, color tables, and contrast checks are unchanged from upstream — refresh from upstream when content changes there.
Runtime contract: every org interaction in this skill is a single REST call dispatched through the Codey runtime (
dispatchlocally / the hosted Headless 360 MCP in shared surfaces). This skill has no dependency on the execution environment — nosfCLI, no shell scripts, no local Python, no temp files. Colors are derived and validated by the agent inline, then written with one sObject PATCH. Do not shell out.
Input contract
One of:
- A website URL — fetch with
WebFetch, extract dominant brand colors. - A brand-guide paste or document — parse for hex codes and named colors.
- Direct hex codes — accept as-is.
- A color description (e.g. "we're a red and white company") — ask for at least one specific hex code or URL before proceeding.
See reference/derivation-methodology.md for the four ingestion cases (A–D) in detail.
Output
A 14-field color scheme written to the org-default FieldServiceMobileSettings record via a single sObject PATCH (PATCH /services/data/vXX.0/sobjects/FieldServiceMobileSettings/{id}). Color changes appear on devices after the metadata cache refreshes (default: 7 days, force-refreshable from app Settings).
Workflow
1. Confirm the target org
Before fetching the brand source, confirm the org is reachable with a cheap auth probe — dispatch SELECT Id FROM Organization LIMIT 1 (GET /services/data/vXX.0/query):
What ships with it
5 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.
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 521a02d032d7
- 7d ago First seen · 134 lines · 135 tokens per session scan A 30199401323f
field-service-mobile-branding-configure is a skill published in the GitHub repository forcedotcom/sf-skills (987 stars, last pushed yesterday), licensed Apache-2.0. It adds 135 tokens to every session and 2,160 once invoked, about $0.0007 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.
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