sf-flex-estimator: Agentforce & Data Cloud Flex Credit Estimation

Use this skill when the user needs a public-price estimate for:

Agentforce prompt + action consumption
Data Cloud monthly usage meters
Flex Credit scenario planning
cost optimization recommendations before build or rollout

This skill is for planning and estimation, not implementation.

When This Skill Owns the Task

Use sf-flex-estimator when the user is asking questions like:

"What will this Agentforce agent cost per month?"
"Estimate Flex Credits for 5 prompts, 8 actions, and Data Cloud grounding"
"Compare low / medium / high usage scenarios"
"How much does Private Connect add?"
"What Flex Credit savings do we get if we reduce streaming or action count?"

Delegate elsewhere when the user is:

building Builder metadata, Prompt Builder templates, or action wiring → sf-ai-agentforce
authoring or fixing .agent files → sf-ai-agentscript
implementing Data Cloud connections, streams, DMOs, segments, or activations → sf-datacloud and the phase-specific sf-datacloud-* skills
creating test data or operational data imports → sf-data
deploying metadata or runtime assets → sf-deploy

Required Context to Gather First

Ask for or infer:

agent prompt count by tier: starter, basic, standard, advanced
action count by type: standard, custom, voice, sandbox
whether token overages are expected for prompts or actions
monthly Data Cloud meter volumes, if Data Cloud is in scope
whether Private Connect is required
whether the estimate should model a pilot, small production, enterprise, or multiple scenarios
whether the user wants public list-price guidance or is trying to reconcile contract-specific commercial numbers

If the user does not know exact monthly volumes, start with a baseline template and generate multiple scenarios.

Core Pricing Model

Agentforce

Agentforce billing is linear — no volume tiers.

Component	FC per invocation
Starter prompt	2
Basic prompt	2
Standard prompt	4
Advanced prompt	16
Standard / custom action	20
Voice action	30
Sandbox action	16

Data Cloud

Data Cloud uses monthly cumulative tiering.

Tier	Monthly FC range	Multiplier
Tier 1	0 - 300K	1.0x
Tier 2	300K - 1.5M	0.8x
Tier 3	1.5M - 12.5M	0.4x
Tier 4	12.5M+	0.2x

Other rules

Flex Credits are priced at $0.004 per FC in this skill.
Private Connect adds 20% of Data Cloud spend after tiering.
Agentforce and Data Cloud are estimated separately, then combined.
Estimates in this skill use publicly documented list pricing only.

For the full meter table and examples, read:

Recommended Workflow

1. Baseline the structure

Model the agent and Data Cloud footprint first.

Useful starting templates:

2. Calculate the per-invocation cost

For Agentforce, estimate:

per-invocation FC = prompt FC + action FC + token overage FC

3. Calculate Data Cloud base FC

Map each monthly meter volume to the current public rate card, then apply cumulative tiering.

4. Generate scenarios

Use the standard scenario set unless the user provides a better one:

Low: 1K invocations / month
Medium: 10K / month
High: 100K / month
Enterprise: 500K / month

5. Validate assumptions and recommend optimizations

Check for:

too many prompts or actions
unnecessary streaming usage
likely token overages
missing Private Connect handling
unrealistic volume assumptions

Scripts and Templates

Calculator

Validation helper

hooks/scripts/validate_estimate.py

This validator is a manual helper. It is intentionally not wired into the shared auto-validation dispatcher because generic .json or .md file patterns would create too much noise.

Example commands

# Per-invocation estimate for a template
python3 assets/calculators/flex_calculator.py \
  --mode structure \
  --agent-def assets/templates/basic-agent-template.json

# Scenario estimate for an Agentforce + Data Cloud design
python3 assets/calculators/flex_calculator.py \
  --mode scenarios \
  --agent-def assets/templates/hybrid-agent-template.json

# Tiering only
python3 assets/calculators/tier_multiplier.py \
  --base-fc 5000000 \
  --pretty

# Validate an estimate input document
python3 hooks/scripts/validate_estimate.py \
  --input assets/templates/hybrid-agent-template.json \
  --verbose

High-Signal Estimation Rules

Prefer standard prompts for most production reasoning workloads.
Use basic prompts only for simple routing/classification.
Action count often dominates cost faster than prompt count.
Data Cloud streaming is materially more expensive than prep/query/segment meters.
Tiering matters only for Data Cloud, not Agentforce.
Private Connect applies only to Data Cloud spend in this model.
If the user has contract-specific pricing, treat this skill as a public baseline and note that commercial terms may differ.

Output Format

When the estimate is complete, present:

workload summary
per-invocation Agentforce cost
monthly scenario table
Data Cloud tiering impact
top optimization recommendations
confidence / validation notes

Suggested shape:

Flex Credit estimate: <name>
Agentforce per invocation: <fc> FC ($<cost>)
Data Cloud monthly base: <fc> FC
Scenarios: <low / medium / high / enterprise>
Optimization priorities: <1-3 bullets>
Confidence: <high / medium / low>

Cross-Skill Integration

Need	Delegate to	Why
build the actual agent metadata	sf-ai-agentforce	implementation of Builder assets
build a deterministic `.agent` bundle	sf-ai-agentscript	authoring and validation of Agent Script
implement Data Cloud pipeline assets	sf-datacloud and `sf-datacloud-*`	live Data Cloud setup
package or deploy the solution	sf-deploy	deployment workflow
generate supporting test or sample data	sf-data	data preparation

A common chain is:

sf-ai-agentforce / sf-ai-agentscript / sf-datacloud-* → sf-flex-estimator → sf-deploy

sf-flex-estimator