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 BanibrataChatterjee/AwesomeSalesforceSkills --skill fsl-scheduling-optimization-designgit clone --depth 1 https://github.com/BanibrataChatterjee/AwesomeSalesforceSkillsWrote 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/banibratachatterjee/awesomesalesforceskills/fsl-scheduling-optimization-design)<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/fsl-scheduling-optimization-design"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/fsl-scheduling-optimization-design/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/banibratachatterjee/awesomesalesforceskills/fsl-scheduling-optimization-design"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/fsl-scheduling-optimization-design.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 | $0.00088 | $0.04058 |
| Opus 5 | $0.00044 | $0.02029 |
| Sonnet 5 | $0.00018 | $0.00812 |
| Haiku 4.5 | $0.00009 | $0.00406 |
Grade A, and why
fsl-scheduling-optimization-design 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FSL Scheduling Optimization Design
This skill activates when a practitioner needs to design or troubleshoot the Field Service Lightning Optimizer — the engine that automatically assigns and sequences service appointments across a workforce. It covers optimization type selection, appointment priority scoring mechanics, travel mode configuration, and optimizer job execution. Use the related fsl-scheduling-policies skill for work rule and service objective configuration.
Before Starting
Gather this context before working on anything in this domain:
- Confirm the Field Service managed package is installed at version 3.x or higher and that the FSL Optimizer is licensed for the org. The Optimizer is a separate licensed component from the base Field Service package; not all Field Service implementations have it.
- Identify the geographic scale of the operation: the number of service territories being optimized, the average appointment density per technician per day, and whether technicians are concentrated or dispersed across a region.
- Determine the scheduling horizon: same-day disruption management requires In-Day optimization, while full-week planning requires Global optimization. The correct type is driven by when decisions are made, not by appointment volume alone.
- Check the org's travel mode configuration in Setup > Field Service Settings > Routing. The default is Aerial (straight-line distance, free). Street-Level Routing is a paid add-on that uses actual road networks and supports predictive traffic data.
- Confirm that service appointments have both
DueDateandPriorityfields populated. Appointments with a nullDueDateare treated as lowest priority by the optimizer and may never be scheduled in a constrained run.
Core Concepts
The Three Optimization Types
FSL provides three distinct optimizer modes. Each is designed for a different decision context and should not be substituted for one another:
Global Optimization processes a batch of unscheduled appointments across a 1–7 day horizon. It is the full-workforce rescheduling engine. Global runs are typically triggered at the start of a day or week to fill the schedule and minimize total travel across the territory. Global optimization can move existing scheduled appointments if re-sequencing improves the overall score. It is the most resource-intensive optimization type and should not be triggered multiple times per hour.
What ships with it
6 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.
- 9d ago First seen · 234 lines · 88 tokens per session scan A 5c77725e9ef5
fsl-scheduling-optimization-design is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 88 tokens to every session and 4,058 once invoked, about $0.0004 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 2026-09-03.
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