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 health-cloud-consent-managementgit 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/health-cloud-consent-management)<a href="https://agentmods.dev/skills/banibratachatterjee/awesomesalesforceskills/health-cloud-consent-management"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/health-cloud-consent-management/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/health-cloud-consent-management"><img src="https://agentmods.dev/badge/skills/banibratachatterjee/awesomesalesforceskills/health-cloud-consent-management.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 | $0.00065 | $0.02397 |
| Opus 5 | $0.00032 | $0.01198 |
| Sonnet 5 | $0.00013 | $0.00479 |
| Haiku 4.5 | $0.00006 | $0.00240 |
Grade A, and why
health-cloud-consent-management 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 — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Health Cloud Consent Management
Use this skill when configuring Health Cloud patient consent management: setting up HIPAA authorization forms, creating consent templates, tracking consent status per patient, and handling withdrawal. This skill covers the clinical consent form lifecycle — template creation, enrollment-linked consent capture, and status management. It does NOT cover marketing consent objects (ContactPointTypeConsent, ContactPointConsent for GDPR/CCPA opt-out), general Experience Cloud consent flows, or consent for non-clinical purposes.
Before Starting
Gather this context before working on anything in this domain:
- Confirm Health Cloud is enabled and Consent Management is configured in Setup. Verify that the DataUsePurpose standard object is available — this is the root of the consent hierarchy.
- Identify the clinical use cases that require HIPAA consent (e.g., treatment, payment, healthcare operations, research). Each becomes a separate DataUsePurpose record.
- Confirm that every AuthorizationForm has at least one AuthorizationFormText with the
IsDefaultflag set to true. A missing default text causes the consent form to silently fail to display during enrollment. - Distinguish clinical consent (HIPAA Privacy Rule authorization) from marketing consent (GDPR/CCPA opt-out). These use completely different object families. Do not confuse AuthorizationFormConsent with ContactPointConsent.
Core Concepts
The Five-Object Consent Hierarchy
Health Cloud patient consent uses a five-object hierarchy:
- DataUsePurpose — Defines the clinical reason PHI is being used (e.g., Treatment, Payment, Research). This is the root anchor of the consent model.
- AuthorizationForm — The form template that describes what the patient is consenting to. One form per consent type (e.g., "HIPAA Authorization for Treatment").
- AuthorizationFormText — The actual text/content of the form in a specific language/locale. Every AuthorizationForm must have exactly one default AuthorizationFormText (
IsDefault = true). Missing this causes the form to fail to display. - AuthorizationFormDataUse — Junction object linking AuthorizationForm to DataUsePurpose. Establishes which clinical use purpose each form covers.
- AuthorizationFormConsent — The per-patient consent record. One record per patient per form with fields:
ConsentGiverId(Individual ID),AuthorizationFormTextId,ConsentCapturedSource(how consent was obtained),Status(Seen, Signed, Rejected), and timestamp.
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 · 176 lines · 65 tokens per session scan A 7c9d0b01db6b
health-cloud-consent-management is a skill published in the GitHub repository BanibrataChatterjee/AwesomeSalesforceSkills (3 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 65 tokens to every session and 2,397 once invoked, about $0.0003 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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