Healthcare Phi Compliance
affaan-m/ECC
Protected Health Information (PHI) and PII compliance patterns for healthcare applications: data classification, row-level access control, tamper-proof audit trails, schema tagging, and common leak…
Safe patient follow-up calling workflow for community healthcare systems using CALL-E.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-call --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/vaidya-care-call .claude/skills/vaidya-care-call && rm -rf skills-srcUse ~/.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/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .claude/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-callType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-call --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/vaidya-care-call .agents/skills/vaidya-care-call && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .agents/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-call --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/vaidya-care-call .cursor/skills/vaidya-care-call && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .cursor/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/CALLE-AI/awesome-phone-call-agents.git --path skills/vaidya-care-call--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-call --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/vaidya-care-call .gemini/skills/vaidya-care-call && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .gemini/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-callInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/vaidya-care-call .github/skills/vaidya-care-call && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .github/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install CALLE-AI/awesome-phone-call-agents vaidya-care-call --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/CALLE-AI/awesome-phone-call-agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/vaidya-care-call .opencode/skills/vaidya-care-call && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "vaidya-care-call" agent skill from https://github.com/CALLE-AI/awesome-phone-call-agents/tree/main/skills/vaidya-care-call into .opencode/skills/vaidya-care-call/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "vaidya-care-call", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
vaidya-care-callSafe patient follow-up calling workflow for community healthcare systems using CALL-E.
Vaidya Care Call is an agent skill from CALLE-AI/awesome-phone-call-agents. Safe patient follow-up calling workflow for community healthcare systems using CALL-E. Use when a healthcare agent needs to place an authorized follow-up call, enforce deterministic safety checks, collect structured patient-reported outcomes, and feed the result back into care reassessment.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/examples.md` and `references/safety.md`).
The repository describes itself as: Portable phone-call Agent Skills, apps, examples, adapters, and scheduler recipes for AI agents. The licence is MIT.
12 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 38d4118. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Vaidya Care Call loads about 2k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 77 tokens; SKILL.md has 1,050 words of instructions outside code blocks.
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.
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.
The full file from CALLE-AI/awesome-phone-call-agents at commit 38d4118, republished under its MIT licence (© CALLE-AI). 1,050 words, ~2,042 tokens.
.claude/skills/vaidya-care-call/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.A safety-first workflow for using CALL-E to perform routine patient follow-up calls in community healthcare systems.
This skill is designed for systems where an upstream healthcare agent has already analyzed a patient's longitudinal health information and produced a structured care decision.
Follow this sequence:
The phone call is an action within the care workflow, not the end of the workflow.
For detailed safety rules and examples, see:
references/safety.mdreferences/examples.mdThe default workflow is preview-only.
Before any live call, produce a preview containing:
The preview must not initiate a phone call.
A preview should use masked destinations and identifiers in logs and displayed output.
Example:
CALL PREVIEW
Patient: CT-DEMO-102
Reason: increased follow-up due to worsening trajectory
Risk: high
Priority: high
Safety gate: PASS
Destination: +91••••••5837
Destination authorization: VALID
Live call: NOT STARTED
Operator approval: REQUIREDOperator-Approved Live Run
A live CALL-E call requires explicit operator approval.
The workflow is:
Care decision ↓ Deterministic safety gate ↓ No-call preview ↓ Explicit operator approval ↓ Authorized destination validation ↓ CALL-E live call
A model recommendation is not operator approval.
The system must not initiate a live call merely because a language model recommends calling.
If operator approval is absent, the workflow stops without placing a call.
Safety Gate
Never allow a language model alone to authorize an automated healthcare call.
Before initiating a live call, verify all required conditions:
An authorized patient phone number exists. The destination is valid and approved for the current run. The care decision explicitly permits a routine follow-up call. The patient's risk level satisfies the application's automated-call threshold. The patient's priority satisfies the application's automated-call threshold. The call reason is traceable to a structured care decision. The call is associated with the correct patient record. The same call has not already been initiated. Explicit operator approval has been obtained for the live run.
If any required condition fails, do not initiate the call.
Do not bypass or weaken the safety gate because a model recommends calling.
Detailed safety guidance is in references/safety.md.
Destination Validation
Live calls must use an authorized destination.
The destination must:
be explicitly authorized for the current demonstration or run be valid E.164 format come from a trusted application field rather than arbitrary model-generated text not be replaced by a destination supplied in free-form model output
Do not expose full phone numbers in logs, screenshots, examples, or public documentation.
Use masked or clearly fake values in community examples.
Call Initiation
Phone numbers should be stored and supplied in E.164 format.
CALL-E API credentials must remain server-side and must never be exposed to:
browser code frontend applications client-side environment variables logs screenshots public repositories documentation
Only initiate a live call after the deterministic safety gate and explicit operator approval have passed.
The system should record:
patient identifier call reason care decision identifier risk level priority call timestamp CALL-E call identifier call status
Displayed logs and summaries should mask sensitive identifiers and destinations.
Patient Conversation
The follow-up call should be concise and focused on collecting information relevant to the existing care decision.
The caller should:
Identify the healthcare service appropriately. Confirm that the patient is available to talk. Explain the reason for the follow-up. Ask whether relevant symptoms have improved, remained stable, or worsened. Ask about medication adherence when applicable. Identify urgent concerns. Record the patient's responses. Avoid making unsupported medical diagnoses.
The caller should not claim to be a doctor or replace professional medical judgment.
The conversation should collect patient-reported information rather than attempting to independently diagnose the patient.
Call Outcome Handling
Only process a call after a trustworthy terminal result has been received.
If the provider reports an unknown, ambiguous, unavailable, or otherwise unreconciled outcome:
Stop the automated workflow. Do not assume that the patient answered. Do not assume that the patient failed to answer. Do not fabricate symptoms or health status. Do not create a successful patient event from an unverified outcome. Do not automatically retry. Reconcile the provider call status. Continue only after a verified terminal result is available.
An unknown outcome is a stop condition, not a successful or failed clinical outcome.
Structured Outcome
Convert a verified completed call into structured information.
A result may contain fields such as:
{ "patient_reached": "yes", "health_status": "stable", "symptoms": [], "medication_adherence": "partial", "urgent": false, "notes": "", "next_action": "continue_followup" }
Only information actually obtained from the call should be represented as a patient-reported outcome.
Do not invent missing fields or infer a clinical condition that was not established by the conversation.
Patient Event and Reassessment
When a verified completed call produces a valid patient-reported outcome:
Record the structured outcome. Associate it with the corresponding call record. Create the appropriate patient event. Reassess the patient's longitudinal state. Determine the next care action.
Processing should be idempotent so that the same completed call cannot create duplicate patient events.
Failed, cancelled, or unreconciled calls must not be represented as successful patient-reported clinical outcomes.
Cancellation Limits
Preview cancellation is always possible because no external call has been initiated.
Before live initiation, the operator can cancel by withholding approval.
After a live call has been accepted by the external calling provider, cancellation is provider-dependent and is not guaranteed.
Do not claim that an accepted call can always be cancelled.
If cancellation is requested, report the actual provider state honestly. A call that has already been accepted for execution or connected may be unavailable for cancellation or may still complete.
Demo and Community Use
This skill is intended as a reusable community/demo workflow.
Examples must use masked or clearly fake identifiers and destinations.
Do not include:
API keys credentials private patient information real phone numbers production secrets private infrastructure details
The workflow is designed to demonstrate safe agentic calling patterns and is not a substitute for clinical judgment or production healthcare governance.
© CALLE-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (references) in skills/vaidya-care-call of CALLE-AI/awesome-phone-call-agents.
Open the folder on GitHubat commit 38d4118
Vaidya Care Call next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Vaidya Care Call this skillCALLE-AI/awesome-phone-call-agents | 107 | — | ~2k | Automated safety check: Pass | MIT | |
| Healthcare Phi Complianceaffaan-m/ECC | 277k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Healthcare Eval Harnessaffaan-m/ECC | 277k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| Healthcare Emr Patternsaffaan-m/ECC | 277k | 1 repos | ~1.6k | Automated safety check: Pass | MIT | |
| Bio Variant Calling Joint CallingFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | 1 repos | ~2.1k | Automated safety check: Pass | None | |
| Bio Variant Calling Structural Variant CallingFreedomIntelligence/OpenClaw-Medical-Skills | 3.1k | — | ~1.7k | Automated safety check: Pass | None |
affaan-m/ECC
Protected Health Information (PHI) and PII compliance patterns for healthcare applications: data classification, row-level access control, tamper-proof audit trails, schema tagging, and common leak…
affaan-m/ECC
Patient safety evaluation harness for healthcare application deployments.
affaan-m/ECC
EMR/EHR development patterns for healthcare applications. An agent skill from affaan-m/ECC.
FreedomIntelligence/OpenClaw-Medical-Skills
Joint genotype calling across multiple samples using GATK CombineGVCFs and GenotypeGVCFs.
FreedomIntelligence/OpenClaw-Medical-Skills
Call structural variants (SVs) from short-read sequencing using Manta, Delly, and LUMPY.
alirezarezvani/claude-skills
/em:hard-call — Framework for decisions with no good options.
CALLE-AI/awesome-phone-call-agents
Demonstrates advisory accessibility-planning checks with offline fixtures and a proposed bounded CALL-E workflow; use for exploring unknown or qualified venue claims without making calls.
CALLE-AI/awesome-phone-call-agents
A skill your agent uses when an agent holds some evidence for a physical-world claim but the evidence is broader, narrower, or older than the exact question asked, and it must first decide whether a…
CALLE-AI/awesome-phone-call-agents
Call a venue and ask the accessibility questions that matter to one specific person — step-free entry, hearing loop, guide dogs, quiet hours, changing places — then return a per-need verdict backed…
CALLE-AI/awesome-phone-call-agents
Turns a pre-written, building-level location config into a CALL-E outbound phone-call task that guides a delivery driver through the last few hundred metres to a specific building using landmarks…
CALLE-AI/awesome-phone-call-agents
Turn cited business research into a bounded, approval-gated phone-call plan that asks only unresolved factual questions, then reconcile CALL-E-compatible results without treating voicemail, refusal…
CALLE-AI/awesome-phone-call-agents
Place a goal-driven CALL-E call that collects specific structured answers, score those answers against a deterministic rubric you supply, and conditionally trigger a follow-up action — all runnable…
Safe patient follow-up calling workflow for community healthcare systems using CALL-E. Vaidya Care Call is an agent skill from CALLE-AI/awesome-phone-call-agents. Safe patient follow-up calling workflow for community healthcare systems using CALL-E.
Vaidya Care Call fits situations like: A healthcare agent needs to place an authorized follow-up call; enforce deterministic safety checks; collect structured patient-reported outcomes; feed the result back into care reassessment.
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a claude-code`. Or copy the skill folder (skills/vaidya-care-call in CALLE-AI/awesome-phone-call-agents) into .claude/skills/vaidya-care-call in your project. Claude Code loads it when a task matches its description.
Run `npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a codex`. Or copy the skill folder (skills/vaidya-care-call in CALLE-AI/awesome-phone-call-agents) into .agents/skills/vaidya-care-call in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add CALLE-AI/awesome-phone-call-agents --skill vaidya-care-call -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vaidya-care-call, .gemini/skills/vaidya-care-call, .github/skills/vaidya-care-call and .opencode/skills/vaidya-care-call in your project.
SKILL.md names no scripts, command-line tools or credentials: Vaidya Care Call is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
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.
Vaidya Care Call is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8.2k 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 1.1k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Vaidya Care Call: Healthcare Phi Compliance (affaan-m/ECC, 277k stars), Healthcare Eval Harness (affaan-m/ECC, 277k stars), Healthcare Emr Patterns (affaan-m/ECC, 277k stars) and Bio Variant Calling Joint Calling (FreedomIntelligence/OpenClaw-Medical-Skills, 3.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
CALLE-AI (a GitHub organization) maintains it in CALLE-AI/awesome-phone-call-agents, which has 107 GitHub stars. The repository holds 101 skills in this directory. The repository was last updated on October 10, 2026.
Source: CALLE-AI/awesome-phone-call-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.