Agent skill

Life Sciences Fieldsalesrep Coordinate

by forcedotcom in forcedotcom/sf-skills

A skill your agent uses to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence.

Apache-2.0Auto-check passedTesting & QA

Install Life Sciences Fieldsalesrep Coordinate

skills CLI
$ npx skills add forcedotcom/sf-skills --skill life-sciences-fieldsalesrep-coordinate -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install forcedotcom/sf-skills life-sciences-fieldsalesrep-coordinate --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/forcedotcom/sf-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/life-sciences-fieldsalesrep-coordinate .claude/skills/life-sciences-fieldsalesrep-coordinate && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
life-sciences-fieldsalesrep-coordinate
GitHub stars
1.1k
Token cost
~5.6k tokens
SKILL.md length
2,420 words
Files
16 (incl. references)
Skills in repo
248
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence.

  • Works in 9 steps: Org Selection (MANDATORY, runs first) → Introduction and Confirmation → Execute Stage 1: Prerequisites Validation → …
  • Run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence
  • SKILL.md covers Scope Guard (evaluate FIRST), Required Inputs, Execution Order (MANDATORY) and Workflow, plus 7 more sections
  • Calls sf and git; reaches github.com and login.salesforce.com

What it does

Life Sciences Fieldsalesrep Coordinate is an agent skill from forcedotcom/sf-skills. Use this skill to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence. Trigger when the user says 'set up Life Sciences Cloud end to end', 'run the full LSC setup', 'orchestrate Life Sciences Cloud configuration', 'complete LSC setup', 'Life Sciences Cloud full install', 'set up Life Sciences Cloud end to end for field sales rep', 'run the full LSC setup for field sales rep', 'orchestrate Life Sciences Cloud configuration for field sales rep', 'complete LSC setup for field…

Its SKILL.md is about 5.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 16 other files, including reference files (for example `references/orchestration-flow.md`, `references/stage-2-starter-config-application-flexipage-mapping.md` and `references/stage-2-starter-config-deploy-commands.md`).

It sits in Testing & QA, covering End-to-end testing and Deployment. The repository describes itself as: Salesforce's curated collection of agent skills for building applications. Optimized for Agentforce Vibes, compatible with all AI tools. The licence is Apache-2.0.

When your agent uses it

  • Run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence
  • The user says set up Life Sciences Cloud end to end
  • Run the full LSC setup
  • Orchestrate Life Sciences Cloud configuration

Example prompts

  • “set up Life Sciences Cloud end to end”
  • “run the full LSC setup”
  • “orchestrate Life Sciences Cloud configuration”
  • “/life-sciences-fieldsalesrep-coordinate”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Org Selection (MANDATORY, runs first)
  2. Introduction and Confirmation
  3. Execute Stage 1: Prerequisites Validation
  4. Execute Stage 2: Starter Config Deploy
  5. Execute Stage 3: Territory Configuration
  6. Execute Stage 4: User Provisioning
  7. Execute Stage 5: Sample Visit Creation
  8. Final Summary
  9. Cleanup (delete the shared source folder ONCE)

What it can do on your machine

Read from SKILL.md and the folder at commit 3c15867. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • sf
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • github.com
    • login.salesforce.com
    • test.salesforce.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Life Sciences Fieldsalesrep Coordinate loads about 5.6k tokens when it runs, and up to ~43k if it reads all its reference files. Until then it costs about 250 tokens; SKILL.md has 2,420 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~250
When it runs · the whole SKILL.md, loaded when a task matches
~5.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~43k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from forcedotcom/sf-skills at commit 3c15867, republished under its Apache-2.0 licence (© forcedotcom). 2,420 words, ~5,615 tokens.

Download SKILL.mdSave it as .claude/skills/life-sciences-fieldsalesrep-coordinate/SKILL.md (or your agent's skills folder). This skill also uses 15 other files; get the full folder from GitHub.
name
life-sciences-fieldsalesrep-coordinate
description
Use this skill to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence. Trigger when the user says 'set up Life Sciences Cloud end to end', 'run the full LSC setup', 'orchestrate Life Sciences Cloud configuration', 'complete LSC setup', 'Life Sciences Cloud full install', 'set up Life Sciences Cloud end to end for field sales rep', 'run the full LSC setup for field sales rep', 'orchestrate Life Sciences Cloud configuration for field sales rep', 'complete LSC setup for field sales rep', or 'Life Sciences Cloud full install for field sales rep'. Executes five stages in order: prerequisites validation, starter config deployment, territory configuration, user provisioning, and sample visit creation — gating each stage on the success of the previous one. DO NOT TRIGGER when: user wants to run only one specific stage (prerequisites, config deploy, territory setup, user provisioning, or visit creation individually).
metadata.version
1.0
metadata.minApiVersion
65.0
metadata.domains
Life Sciences
metadata.relatedSkills
life-sciences-prerequisites-validate, life-sciences-territory-configure

Life Sciences Cloud End-to-End Orchestrator

Runs the complete Life Sciences Cloud setup workflow as five stages in strict sequence, gating each on the success of the previous stage. Each stage delegates to a child skill or a reference workflow, organized internally into phases and steps (defined under Execution Order below).

Scope Guard (evaluate FIRST)

Serve only requests for the full end-to-end LSC setup. A single stage/phase/step is never invokable here — never silently expand a partial ask into the whole flow. Before any work:

  • Unrelated to LSC setup (at start or mid-run) → do not attempt it. Tell the user you did not understand the request and show what you can help with (full end-to-end LSC setup, or standalone life-sciences-prerequisites-validate / life-sciences-territory-configure); stop.
  • Stage with its own standalone skill — prerequisites (Stage 1) or territory config (Stage 3) → redirect to life-sciences-prerequisites-validate / life-sciences-territory-configure; stop.
  • Stage with no standalone skill — config deploy (2), user provisioning (4), visit creation (5) → explain these run only as part of the full flow, not on their own; stop. Do not launch the full flow unless the user then asks for it.

Continue only for the complete end-to-end setup: orchestrating the full flow (prerequisites → config deploy → territory → user provisioning → visit creation) in order with gates. Each stage's actual work is delegated to child skills / reference files.


Required Inputs

Gather before proceeding:

  • Target org: The org to deploy to — selected by the user from the list of connected orgs, or a freshly authenticated org (see Phase 0). Never assume a default org silently; always have the user confirm or select the target org before any stage runs.

Execution Order (MANDATORY)

Terminology: Stage = one of the 5 units of work (1–5), each delegated to a child skill or a reference workflow; Phase = a named group of work inside a stage; Step = an atomic action inside a phase. So "Stage 2 › Phase 1 › Step 3" reads top-to-bottom.

Run in this order, each gated on the previous (see the full dependency diagram in references/orchestration-flow.md):

#StageRunsGate (must pass to advance)Output
—Setup: download .lsc-starter-config/LSStarterConfig—Folder present (MANDATORY — hard stop)Shared source folder in CWD
1Prerequisites Validationlife-sciences-prerequisites-validate skillAll prerequisites PASSOrg confirmed ready
2Starter Config Deployreferences/stage-2-starter-config-overview.mdAll 13 deploy steps succeedLSC Custom Profile exists
3Territory Configurationlife-sciences-territory-configure skillTerritory model Active + L3 territoryLevel-3 territory ID + name
4User Provisioningreferences/stage-4-user-provisioning-overview.mdUser created, permsets + territory assignedRep username
5Sample Visit Creationreferences/stage-5-visit-creation-overview.mdVisit + supporting records created; metadata cache generated—

Workflow

Phase 0 — Org Selection (MANDATORY, runs first)

Before presenting the workflow, establish which org to use. Do this every time the user asks to set up Life Sciences Cloud — do not silently reuse the current default org.

  1. List connected orgs:

    bash
    sf org list --json

    Parse the result and present the authenticated orgs (non-expired) to the user as a numbered list — include alias, username, org type (Dev Hub / Sandbox / Scratch / Production), and the default marker if any:

    text
    Connected Orgs — select the target for Life Sciences Cloud setup
    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
      1. ls-dev        alice@example.com          (Dev Hub)   [default]
      2. ls-sandbox    alice@example.com.sandbox  (Sandbox)
      3. partial-scr   test-xyz@example.com       (Scratch)
    
      N. Log in to a fresh org (opens a browser to authenticate a new org)
  2. Ask the user to choose: "Which org would you like to use? Enter a number, or choose N to log in to a fresh org."

  3. Handle the selection:

    • Existing org chosen → capture its username/alias as the target org for all subsequent steps.

    • Fresh org chosen (option N) → authenticate a new org interactively: ask for the login URL (My Domain / instance URL, e.g. https://mydomain.my.salesforce.com; https://login.salesforce.com for production, https://test.salesforce.com for a sandbox) and an alias (e.g. ls-setup), then run the login command yourself:

      bash
      sf org login web --instance-url <user-supplied-url> --alias <user-supplied-alias> --set-default

      Do not hand the command to the user to run — execute it directly. It opens a browser on the user's machine for them to complete the web login interactively; the command then returns. After it finishes, re-run sf org list --json to confirm the new org, then use it as the target org.

  4. Confirm the target org back to the user before proceeding: "Using <alias> (<username>) as the target org for Life Sciences Cloud setup." Store this in OrchestrationState.targetOrg.

If sf org list returns no authenticated orgs, go straight to the fresh-org login flow (option N) — there is nothing to select from.

Phase 1 — Introduction and Confirmation
  1. Present the workflow to the user:

    text
    Life Sciences Cloud — Full Setup Workflow
    ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
    
    This will execute 5 stages in sequence. Each stage is internally
    organized into phases and steps.
    
    Stage 1: Validate Prerequisites
             Checks org settings, permissions, and features
    
    Stage 2: Deploy Starter Configuration
             Deploys objects, profiles, config records, layouts, flexipages
    
    Stage 3: Configure Territories
             Creates territory type, model, and 3-level hierarchy
    
    Stage 4: Provision Field Sales Rep User
             Creates user, assigns profile/permsets, assigns to territory
    
    Stage 5: Create Sample Visit
             Logs in as the rep, creates account/provider/visit records,
             generates the mobile metadata cache
    
    Target org: <org>
  2. Ask for confirmation: "Ready to begin the full Life Sciences Cloud setup? (yes/no)"

  3. Download the shared source folder ONCE (MANDATORY — hard gate, before any stage). Both Stage 2 (Starter Config Deploy — metadata + config records) and Stage 5 (Sample Visit Creation — Data CSVs) read from .lsc-starter-config/LSStarterConfig/; those stages do NOT download or delete it — the orchestrator owns a single download here and a single delete in Phase 8. Sparse-checkout only that subtree (the repo is large) into the CWD:

    bash
    git clone --no-checkout --depth 1 --filter=blob:none \
      https://github.com/SalesforceLabs/LSStarterConfig.git lsstarter-tmp
    cd lsstarter-tmp && git sparse-checkout init --cone \
      && git sparse-checkout set Codey/LSStarterConfig && git checkout && cd ..
    mv lsstarter-tmp/Codey ./.lsc-starter-config && rm -rf lsstarter-tmp

    .lsc-starter-config/LSStarterConfig/ contains its own sfdx-project.json (pins sourceApiVersion: 65.0) — the deploy step (Phase 3) must run from inside it. If the folder already exists in the CWD (from a prior run), reuse it (skip the download).

  4. Download gate — verify the folder exists before proceeding. Confirm the download succeeded by checking that .lsc-starter-config/LSStarterConfig/sfdx-project.json and .lsc-starter-config/LSStarterConfig/Data/ are present (e.g. ls .lsc-starter-config/LSStarterConfig/sfdx-project.json .lsc-starter-config/LSStarterConfig/Data).

    • If present → set sourceFolderDownloaded: true in OrchestrationState and proceed to Phase 2.

    • If the download failed or the folder/contents are missing → STOP. Do NOT proceed to any stage — every stage depends on this folder. Report the failure and stop:

      text
      STOP: Setup cannot start — source download failed
      
      Could not download .lsc-starter-config/LSStarterConfig from
      https://github.com/SalesforceLabs/LSStarterConfig.git
      Likely: no network / GitHub unreachable, git < 2.25 (no sparse-checkout),
      or insufficient disk space / write permission in the CWD.
      
      Mandatory prerequisite — no stage can run without it. Fix the cause and
      re-run, or download the folder manually into the CWD, then re-run.

      Leave sourceFolderDownloaded: false and do not advance the workflow.

Phase 2 — Execute Stage 1: Prerequisites Validation
  1. Run the prerequisites validation following the life-sciences-prerequisites-validate skill workflow exactly.

  2. Gate check: Review the results.

    • If ALL prerequisites pass → proceed to Stage 2
    • If ANY prerequisite fails → stop and present the failure report
    text
    STOP: Stage 1 FAILED — Prerequisites not met
    
    <show the prerequisite failure table>
    
    Please resolve the failed prerequisites and re-run this workflow.

    Ask the user: "Would you like to continue anyway (skip failed prerequisites), or stop and fix them first?"

    • If user says stop → end the workflow
    • If user says continue → proceed with a warning that later stages may fail
Phase 3 — Execute Stage 2: Starter Config Deploy
  1. Run the starter config deployment following references/stage-2-starter-config-overview.md exactly (all 13 steps in order); read its own reference files as directed.

  2. Gate check: Verify the LSC Custom Profile exists:

    bash
    sf data query --query "SELECT Id, Name FROM Profile WHERE Name = 'LSC Custom Profile'" --target-org <org> --json
    • If profile exists → proceed to Stage 3
    • If profile not found → stop and report deployment failure
Phase 4 — Execute Stage 3: Territory Configuration
  1. Run the territory configuration following the life-sciences-territory-configure skill workflow exactly.

  2. Gate check: Verify the territory model is Active and level-3 territory exists:

bash
sf data query --query "SELECT Id, Name, DeveloperName, Territory2Model.State FROM Territory2 WHERE ParentTerritory2.ParentTerritory2Id != null AND Territory2Model.State = 'Active'" --target-org <org> --json
  • If level-3 territory found with Active model → capture the territory ID and name, proceed to Stage 4
  • If not found → stop and report the issue
Phase 5 — Execute Stage 4: User Provisioning
  1. Run the user provisioning following references/stage-4-user-provisioning-overview.md exactly; read its own reference file as directed. Pass the territory information captured from Stage 3.

  2. Gate check: Verify the user exists, has the correct profile, all 4 permission sets, and territory assignment. Capture the rep username — Stage 5 logs in as this user.

    STOP-GATE (Stage 4 completeness). Do NOT accept "user created" as passing this gate — verify all four facets and STOP if any is short:

    bash
    sf data query --query "SELECT COUNT(Id) c FROM PermissionSetAssignment WHERE AssigneeId = '<newUserId>' AND PermissionSet.IsOwnedByProfile = false" --target-org <org> --json

    The permset count MUST be 4 ({LifeSciencesCore, LifeSciencesFieldSalesRepresentative, HealthCloudStarter, LifeSciencesKeyAccountManager}); the user MUST be IsActive=true on the LSC Custom Profile; and a UserTerritory2Association to the level-3 territory MUST exist. If the permset count is < 4 or any facet is missing, Stage 4 did not fully complete — re-run the missing part of references/stage-4-user-provisioning-overview.md (its own Phase 4/5 stop-gates cover this) before advancing to Stage 5. A rep missing a permset silently fails visit creation downstream with confusing permission errors.

Show full SKILL.md (1,114 more words)Show less
Phase 6 — Execute Stage 5: Sample Visit Creation
  1. Run the visit creation following references/stage-5-visit-creation-overview.md exactly; read its own reference files as directed. Pass the rep username captured from Stage 4. This stage:

    • Logs in as the rep user (sf org login web) and creates account, healthcare provider, and visit records (rep-owned), plus territory associations and product master data (admin-owned).
    • Generates the mobile metadata cache via the Connect API (admin-owned).

    This stage uses two identities — the rep user (from Stage 4) for visit records and the admin for product master data and metadata cache generation. Follow the child skill's rep/admin split exactly.

  2. Gate check: Verify at least one Visit record was created:

    bash
    sf data query --query "SELECT Id, Name, AccountId FROM Visit ORDER BY CreatedDate DESC LIMIT 1" --target-org <org> --json
    • If a Visit exists → proceed to the final summary
    • If no Visit found → stop and report the visit-creation failure
Phase 7 — Final Summary
  1. Display the complete workflow summary — a "Life Sciences Cloud Setup Complete" header followed by one block per stage (substitute actual values from the run):

    • Stage 1: all org prerequisites confirmed.
    • Stage 2: objects/profiles/config records deployed, <N> layouts + <N> flexipages deployed, 28 trigger handlers activated.
    • Stage 3: Territory Model <model name> (Active); Level-3 Territory <territory name>.
    • Stage 4: User <firstName> <lastName> (<username>); Profile LSC Custom Profile; permission sets Life Sciences Core, Life Sciences Field Sales Representative, Health Cloud Starter, Life Sciences Key Account Management; Territory <territory name>; admin also assigned to the territory.
    • Stage 5: Account + Healthcare Provider created; Visit <name> (Territory <territory name>); product detailing/discussion records; mobile metadata cache generated (Connect API).

    Close with: "The org is ready for Life Sciences Cloud field sales workflows."

Phase 8 — Cleanup (delete the shared source folder ONCE)
  1. After the final summary (all 5 stages complete), delete the .lsc-starter-config folder downloaded in Phase 1 to leave the working directory clean. Run from the CWD (the parent of .lsc-starter-config/):

    bash
    rm -rf .lsc-starter-config

    Do this silently — do NOT print a cleanup line or mention the folder deletion in the final output. Skip if the workflow stopped on a failure and the user may resume — keep the folder until the flow completes so a resumed stage can still read it. This is the single deletion for the whole flow; the child skills never delete it.


State Tracking

Maintain overall orchestration state:

text
OrchestrationState = {
  targetOrg: string,
  sourceFolderDownloaded: boolean,   // .lsc-starter-config/LSStarterConfig downloaded in Phase 1, deleted in Phase 8
  stages: [
    { name: "Prerequisites", status: "pending|running|passed|failed|skipped" },
    { name: "StarterConfig", status: "pending|running|passed|failed" },
    { name: "TerritorySetup", status: "pending|running|passed|failed", territoryId?: string, territoryName?: string },
    { name: "UserProvisioning", status: "pending|running|passed|failed", userId?: string, username?: string },
    { name: "VisitCreation", status: "pending|running|passed|failed", visitId?: string }
  ]
}

Idempotent Stage Transitions & Mid-Flow Changes

Stages are not re-entrant. Before executing any stage, check its status in OrchestrationState: running → reply "Stage N is already in progress" and take no action; passed → ask for explicit confirmation before re-running; failed → re-run (intentional recovery); pending → advance. Transition status to running at execution start (not on user input) so accidental double-confirms never run a stage twice.

If the user requests a change to an earlier stage's inputs while a later stage is in progress or pending, run an impact assessment first: acknowledge without applying, identify affected vs. unaffected stages, present options (re-run affected / apply going forward only / cancel), and wait for the decision. Surface destructive-change warnings (an activated territory model can't be deleted; an existing user/records remain).

The full behavior matrix, impact-assessment template, per-change impact mapping, and destructive-change warnings are in references/state-machine-and-changes.md.


Rules / Constraints

ConstraintRationale
Always run Phase 0 org selection first; list connected orgs and let the user pick or log in to a fresh orgUser must explicitly choose the target org; never silently reuse the default
Download .lsc-starter-config/LSStarterConfig exactly once (Phase 1, MANDATORY hard gate) and delete it exactly once (Phase 8); child skills never download or delete itBoth child skills read from the shared folder — proceeding without it guarantees downstream failures
Execute stages strictly in order 1→5, gating each on prior successEach stage depends on outputs from previous stages; prevents cascading failures
Never skip Stages 2 or 3, or Stage 4 before Stage 5User provisioning depends on profile + territory; visit creation logs in as the Stage-4 rep
Follow each child skill's workflow exactly; capture outputs (IDs, names) for later stagesChild skills have their own confirmations; avoids redundant re-queries
Never re-execute a running/passed stage without explicit confirmation; transition status to running at execution start, not on user inputRace-free idempotency against duplicate "Proceed" messages
Perform impact assessment before applying mid-flow changesUser must see what will break/redo before committing to a change

Gotchas

IssueResolution
Source download fails in Phase 1 (network/git/disk)Hard stop — do NOT run any stage. Report the failure (see Phase 1 download gate); fix the cause or download .lsc-starter-config/LSStarterConfig manually into the CWD, then re-run
No connected orgs foundsf org list returns none — go straight to the fresh-org login (sf org login web) in Phase 0
Fresh-org / rep login needs a browserRun sf org login web yourself (Phase 0 org auth, Stage 5 rep login) — don't hand it to the user. It opens a browser on the user's machine; they complete the web login there and the command returns
Artifacts exist from a prior run (profile, territory, user, config)The child skills are idempotent/upsert-safe and detect existing records — query the org to confirm, then skip or re-run safely
Visit creation uses two identities (rep + admin)Product master data and metadata cache are admin-owned; follow the child skill's rep/admin split
Stage re-triggered, or user changes an earlier input mid-flowSee the transition matrix and impact assessment in references/state-machine-and-changes.md

Resume / Partial Re-run

If the user may have already completed some stages (e.g. from a prior session), ask which, then verify each claimed-complete stage by querying the org (Stage 1 = ask; 2 = LSC Custom Profile; 3 = active model + L3 territory; 4 = user with correct profile/permsets; 5 = a Visit record). Skip verified stages and resume from the first incomplete one. Exact detection queries per stage are in references/orchestration-flow.md → Resume Logic.


Output Expectations

Deliverables:

  • .lsc-starter-config/LSStarterConfig folder downloaded once (Phase 1) and removed once (Phase 8) — both done silently; not reported in the final summary
  • All 5 stages executed successfully (or user-acknowledged skips)
  • Full summary of what was created/configured
  • Org ready for Life Sciences Cloud field sales workflows

Reference File Index

FileWhen to read
references/orchestration-flow.mdAt start — the dependency diagram, per-stage gate verification queries, resume-detection queries, and timing expectations
references/state-machine-and-changes.mdWhen a stage is re-triggered or the user changes an earlier input mid-flow — the full transition behavior matrix, impact-assessment template + mapping, and destructive-change warnings
references/stage-2-starter-config-overview.mdDuring Stage 2 (Phase 3) — the full 13-step starter-config deploy workflow; it points to its own sibling references as needed
references/stage-4-user-provisioning-overview.mdDuring Stage 4 (Phase 5) — the full field-sales-rep user provisioning workflow; it points to its own sibling reference as needed
references/stage-5-visit-creation-overview.mdDuring Stage 5 (Phase 6) — the full sample-visit creation workflow; it points to its own sibling references as needed

© forcedotcom, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 15 other files (references) in skills/life-sciences-fieldsalesrep-coordinate of forcedotcom/sf-skills.

  • SKILL.md
  • references/orchestration-flow.md
  • references/stage-2-starter-config-application-flexipage-mapping.md
  • references/stage-2-starter-config-deploy-commands.md
  • references/stage-2-starter-config-lifesci-metadata-deploy.md
  • references/stage-2-starter-config-overview.md
  • references/stage-2-starter-config-profile-layout-assignments.md
  • references/stage-2-starter-config-state-tracking.md
  • references/stage-2-starter-config-trigger-handlers.md
  • references/stage-4-user-provisioning-overview.md
  • references/stage-4-user-provisioning-user-provisioning-details.md
  • references/stage-5-visit-creation-execution-state-and-recovery.md
  • references/stage-5-visit-creation-metadata-cache-generation.md
  • references/stage-5-visit-creation-overview.md
  • references/stage-5-visit-creation-visit-creation-data.md
  • references/state-machine-and-changes.md

Open the folder on GitHubat commit 3c15867

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Questions about Life Sciences Fieldsalesrep Coordinate

What does Life Sciences Fieldsalesrep Coordinate do?

A skill your agent uses to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence. Life Sciences Fieldsalesrep Coordinate is an agent skill from forcedotcom/sf-skills. Use this skill to run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence.

When should I use Life Sciences Fieldsalesrep Coordinate?

Life Sciences Fieldsalesrep Coordinate fits situations like: run the full end-to-end Life Sciences Cloud setup workflow for field sales rep in sequence; the user says set up Life Sciences Cloud end to end; run the full LSC setup; orchestrate Life Sciences Cloud configuration.

How do I install Life Sciences Fieldsalesrep Coordinate in Claude Code?

Run `npx skills add forcedotcom/sf-skills --skill life-sciences-fieldsalesrep-coordinate -a claude-code`. Or copy the skill folder (skills/life-sciences-fieldsalesrep-coordinate in forcedotcom/sf-skills) into .claude/skills/life-sciences-fieldsalesrep-coordinate in your project. Claude Code loads it when a task matches its description.

How do I install Life Sciences Fieldsalesrep Coordinate in Codex?

Run `npx skills add forcedotcom/sf-skills --skill life-sciences-fieldsalesrep-coordinate -a codex`. Or copy the skill folder (skills/life-sciences-fieldsalesrep-coordinate in forcedotcom/sf-skills) into .agents/skills/life-sciences-fieldsalesrep-coordinate in your project. Codex loads it when a task matches its description.

Can I use Life Sciences Fieldsalesrep Coordinate in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add forcedotcom/sf-skills --skill life-sciences-fieldsalesrep-coordinate -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/life-sciences-fieldsalesrep-coordinate, .gemini/skills/life-sciences-fieldsalesrep-coordinate, .github/skills/life-sciences-fieldsalesrep-coordinate and .opencode/skills/life-sciences-fieldsalesrep-coordinate in your project.

What does Life Sciences Fieldsalesrep Coordinate need to run?

Going by SKILL.md and its folder, Life Sciences Fieldsalesrep Coordinate needs the command-line tools its instructions call (sf and git).

Does Life Sciences Fieldsalesrep Coordinate access the network?

SKILL.md names 3 domains. In commands or code: github.com, login.salesforce.com and test.salesforce.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Life Sciences Fieldsalesrep Coordinate safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Life Sciences Fieldsalesrep Coordinate use?

Life Sciences Fieldsalesrep Coordinate is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Life Sciences Fieldsalesrep Coordinate use?

About 5.6k tokens (SKILL.md is roughly 22k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 38k tokens, read only when the agent opens those files.

What are the alternatives to Life Sciences Fieldsalesrep Coordinate?

Skills that share tags, products or a category with Life Sciences Fieldsalesrep Coordinate: E2E Deploy Rhdh (redhat-developer/rhdh, 172 stars), Deployment E2E Testing (microsoft/aspire, 6.3k stars), OpenWork Release Validation (different-ai/openwork, 24k stars) and Vss E2E Smoke (open-edge-platform/edge-ai-libraries, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Life Sciences Fieldsalesrep Coordinate?

forcedotcom (a GitHub organization) maintains it in forcedotcom/sf-skills, which has 1,058 GitHub stars. The repository holds 248 skills in this directory. The repository was last updated on October 3, 2026.

Source: forcedotcom/sf-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.