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Extract and summarize medication inventories from packaged synthetic clinical evidence.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "clinical-notes-summarizer-medication-inventory" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/aibast-agents-library/main/solutions/clinical-notes-summarizer/manual/skills/medication-inventory/SKILL.md 2. Save it as ~/.claude/skills/medication-inventory/SKILL.md 3. Reload skills and tell me it's ready
List the source-recorded medications for SYN-ENC-001 for reconciliation, preserving the original order, statuses, dates, and values exactly.
A “# Medication Source Inventory” output with medications from the source records and a clinician/pharmacist review line.
Retrieve the medication inventory for SYN-ENC-999; if the identifier or evidence is missing, state what is missing and list the known synthetic identifiers.
If no matching record exists, clearly state the missing identifier or evidence and return the known available synthetic record IDs.
Using the packaged knowledge files, output the medication source inventory for SYN-ENC-001. Do not infer interactions or alter any uncertainty wording.
The result preserves original identifiers, names, headings, uncertainty, and source ordering without extra medical inference.
Researchers or analysts can extract the source-recorded medication list for a specified synthetic encounter to reconcile records. The workflow is read-only and does not modify any record.
When a fixed-format medication inventory is needed, this skill returns the required heading, medication order, and human review line. It emphasizes preserving original dates, statuses, and values without added inference.
If the requested synthetic identifier does not exist, the skill explains what is missing and lists known synthetic identifiers instead of substituting another record. This helps avoid using the wrong case.
The README describes a Clinical Notes Agent workflow for producing a medication source inventory from synthetic evidence. It routes equivalent requests to the same task, uses two packaged knowledge files, and only returns the exact synthetic identifier requested. The output must follow a fixed format, preserve original names, dates, values, statuses, uncertainty, and source order, and avoid inferring interactions. If data is missing, it should report what is missing and list known synthetic identifiers.
List the source-recorded medications for SYN-ENC-001 for reconciliation.
Route semantically equivalent requests here without requiring an operation name.
Use both packaged knowledge files. Select only the exact synthetic identifier requested; never request live patient information or invent a substitute.
# Medication Source Inventory; exact medications in order and clinician/pharmacist review line. Do not infer interactions.
Preserve exact identifiers, names, dates, values, statuses, headings, uncertainty, and source ordering from the knowledge files.
This is read-only synthetic evidence. Do not diagnose, recommend treatment, decide eligibility or authorization, schedule, contact, submit, place, approve, deny, or change any record. Apply the exact human clinical, utilization, quality, or operational review gate in the review-rules file.
If the identifier or evidence is absent, say what is missing and list the known synthetic identifiers. Do not substitute another record.
It reproduces a deterministic medication-inventory workflow from packaged synthetic clinical evidence. For a specified synthetic identifier, it outputs the source-recorded medications for reconciliation.
No. The documentation states this is a read-only synthetic-evidence workflow and does not diagnose, recommend treatment, approve, submit, or change records, and it does not infer drug interactions.
If the identifier or evidence is missing, it states what is missing and lists the known synthetic identifiers. It does not substitute another record for the requested one.
Checks claim-file readiness and compiles evidence for human review.
Analyze client engagement signals across meetings, escalations, billing, and utilization.
Triages fictional insurance claims and summarizes key intake details and priority.
Compare incentive options by synthetic cost, modeled lift, and net value.
Estimate policy-term settlement, coverage limits, and deductibles for claims processing.
Segment a fictional client portfolio and visualize health and churn indicators.
Generate source-grounded encounter summaries from packaged synthetic clinical evidence.
Extract a source-coded problem list from synthetic clinical evidence deterministically.
Extract referral context and missing actions from synthetic clinical note evidence.
Check drug interactions, dose ranges, and allergy cross-reactivity safely.
Generate SOAP notes, billing codes, and visit summaries from clinical audio.
Enable AI to review medications, schedule visits, and identify care gaps.