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Creates a deterministic reconsideration evidence packet from synthetic source files.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "prior-authorization-appeal-evidence-packet" skill from askskill: 1. Download https://raw.githubusercontent.com/microsoft/aibast-agents-library/main/solutions/prior-authorization/manual/skills/appeal-evidence-packet/SKILL.md 2. Save it as ~/.claude/skills/appeal-evidence-packet/SKILL.md 3. Reload skills and tell me it's ready
Generate a minimum-necessary reconsideration evidence outline for SYN-AUTH-001, preserving original headings, IDs, dates, values, statuses, and source order.
Outputs a '# Reconsideration Evidence Draft' with reviewer confirmation, source state, policy reference, and minimum-necessary evidence.
If SYN-AUTH-001 evidence is missing, state what is missing and list the known synthetic identifiers; do not substitute another record.
Returns a missing-items note and a list of known synthetic identifiers.
Only perform read-only evidence preparation: do not diagnose, recommend treatment, decide eligibility, submit, or modify any record; output only the reconsideration evidence draft.
Generates a read-only evidence packet that stays within review boundaries and contains no treatment or authorization decisions.
Operations, documentation, or research users can turn synthetic evidence into a consistent reconsideration draft. It preserves exact identifiers and source order for human review.
When users want to confirm whether a synthetic identifier has supporting evidence, this skill reports missing items and lists known identifiers.
Useful when strict review boundaries matter: it compiles evidence only, without diagnosis, approval, denial, or record changes.
The document defines a prior-authorization reconsideration evidence workflow for a specific synthetic identifier and two packaged knowledge files. The output must include a fixed title, reviewer confirmation, source state, policy reference, minimum-necessary evidence, and human ownership. It requires preserving exact identifiers, dates, values, statuses, and source order, while staying read-only and avoiding diagnosis, treatment advice, authorization decisions, or record changes. If evidence is missing, it should state what is missing and list known synthetic identifiers.
Prepare a minimum-necessary reconsideration evidence outline for SYN-AUTH-001.
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.
# Reconsideration Evidence Draft; reviewer confirmation, source state, policy reference, minimum-necessary evidence, and human ownership.
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 turns packaged synthetic evidence into a reconsideration evidence draft for prior authorization. The output follows a fixed contract and preserves exact source details.
It requires the packaged knowledge files and the exact synthetic identifier requested, such as SYN-AUTH-001. It only works from these synthetic sources and does not request real patient information.
No. It is a read-only reconsideration evidence workflow and does not diagnose, recommend treatment, decide eligibility, submit, approve, deny, or modify records.
Summarize recovery conversion metrics with benchmarks, forecasts, and assumptions.
Identify at-risk client accounts and suggest recovery actions with risk context.
Generate a synthetic points summary explanation without changing the ledger.
Prioritize churn reviews with transparent evidence and suggested next steps.
Review SIU indicators in claims and return explainable evidence with human review guidance.
Compare packaged satisfaction and NPS trends to identify declining accounts.
Generates a criteria-to-evidence crosswalk from packaged synthetic authorization evidence.
Extract referral context and missing actions from synthetic clinical note evidence.
Generate source-grounded encounter summaries from packaged synthetic clinical evidence.
Checks claim-file readiness and compiles evidence for human review.
Extract and summarize medication inventories from packaged synthetic clinical evidence.
Draft prioritized cross-sell recommendations and a reviewable engagement plan from synthetic data.