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 einstein-discovery-setupgit 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/einstein-discovery-setup)<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/einstein-discovery-setup"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/einstein-discovery-setup/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/einstein-discovery-setup"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/einstein-discovery-setup.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 | $0.00126 | $0.03692 |
| Opus 5 | $0.00063 | $0.01846 |
| Sonnet 5 | $0.00025 | $0.00738 |
| Haiku 4.5 | $0.00013 | $0.00369 |
Grade A, and why
einstein-discovery-setup 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 — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Einstein Discovery Setup
Use this skill when an admin needs to configure Einstein Discovery through the CRM Analytics Studio wizard interface — creating stories, deploying prediction definitions, setting up writeback fields on Salesforce objects, enabling what-if analysis for recommendations, and managing model refresh and activation. This skill covers the point-and-click admin path only. For the developer API path (programmatic scoring, bulk predict jobs, REST endpoint integration), use the einstein-discovery-development skill instead.
Before Starting
Gather this context before working on anything in this domain:
- CRM Analytics license: Einstein Discovery requires a CRM Analytics (formerly Tableau CRM) license. It is not available in orgs without this license. Confirm provisioning in Setup > Company Information > Licenses before starting. This is a distinct license from Einstein Prediction Builder, which does not require CRM Analytics.
- Admin surface: Story creation happens in CRM Analytics Studio, not in the main Setup menu. Navigate to App Launcher > Analytics Studio > Create > Story. Admins who look in Setup > Einstein > Einstein Discovery will not find the story wizard there.
- Writeback field limits: Einstein Discovery supports a maximum of three writeback fields per Salesforce entity (object). If the org already has three writeback fields on the target object, a new one cannot be created without removing an existing one.
- Model activation is not automatic: After a model refresh job completes, the new model version is NOT automatically activated. Scoring continues against the prior model version indefinitely until an admin explicitly activates the new version on the prediction definition. There is no error or warning in the UI when this happens.
Core Concepts
Story Creation Wizard — Three Steps
Einstein Discovery story creation follows a three-step wizard in CRM Analytics Studio:
- Define the outcome variable: Choose whether to maximize, minimize, or predict a binary outcome on the target field. Binary outcome (true/false, won/lost, converted/not) uses classification models. Numeric outcomes (revenue, score) use regression models. This step also selects the target Salesforce object.
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 · 221 lines · 126 tokens per session scan A 88d2ef4e853d
einstein-discovery-setup is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 126 tokens to every session and 3,692 once invoked, about $0.0006 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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