med-reconcile

med-reconcile is a skill for Claude Code, Codex from microsoft/cat-agent-skills. It costs 134 tokens per session (1,562 once invoked), scanned A, original, MIT.

A report that compares the admission, inpatient-change, and planned discharge medicine lists. It identifies medicines started, stopped, or changed and flags differences that remain unresolved, but it does not apply corrections or decide whether a medicine is clinically suitable.

In plain words
What is it for?
It helps check home medicines, inpatient starts or stops, dose or treatment changes, reasons, and unresolved differences in a discharge medication list.
Why use it?
Medication lists can change during a hospital stay and errors can be carried into discharge paperwork. This shows whether the planned list matches the documented record before it is used in later documents.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit It helps check home medicines, inpatient starts or stops, dose or treatment changes, reasons, and unresolved differences in a discharge medication list.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microsoft/cat-agent-skills/med-reconcile
About the project

microsoft/cat-agent-skills is a static website that catalogs reusable instruction sets and related packages for AI agents. People use it to search, filter, rate, and download skills for Cowork, Copilot Studio, and Scout, along with Copilot plugins and Scout automations. The catalogue entries are the skills, instructions, plugins, and settings displayed by the site.

microsoft/cat-agent-skills · 101 stars · on GitHub

Install

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.

Any agent
npx skills add microsoft/cat-agent-skills --skill med-reconcile
Clone the repo
git clone --depth 1 https://github.com/microsoft/cat-agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for med-reconcile

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/med-reconcile/github.svg)](https://agentmods.dev/skills/microsoft/cat-agent-skills/med-reconcile)
Your own site
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/med-reconcile"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/med-reconcile/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.

agentmods 80×15 button for med-reconcile

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/cat-agent-skills/med-reconcile"><img src="https://agentmods.dev/badge/skills/microsoft/cat-agent-skills/med-reconcile.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 134 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,562 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00134 $0.01562
Opus 5.5 $0.00054 $0.00625
Sonnet 5.5 $0.00027 $0.00312
Haiku 4.5 $0.00013 $0.00156

Measured 2d ago against content hash 6862e5a2ee4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

med-reconcile 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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (base/scripts/med_reconcile.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

submissions/discharge-care-transition/med-reconcile/SKILL.md · 82 lines

How it starts

The opening of the file, as written. The whole thing — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Med Reconcile

Action level: L0 (read and analyse only). The diff is reported, never applied; nothing is ordered or filed.

Purpose

Prove the discharge medication list is safe before it is drafted into the summary.

When to use

After admission-synthesise, whenever a discharge medication list is being prepared. Typical triggers: "reconcile the discharge meds", "check the discharge medication list", "did anything get stopped during the stay", "just pull the home med list forward as-is".

When NOT to use

When NOT to use: do not use it to draft or edit any prose (summary-draft, patient-instructions), to build the follow-up list (followup-plan), or to apply a correction to draft_discharge_meds - it is a report, not a fix. Do not use it as a clinical decision aid: it does not judge whether a medication is appropriate, only whether the draft matches the documented record. Do not run it on a partial medication list to get an early "clean" - an incomplete list is escalated, not reconciled.

Inputs

admission_meds; inpatient_changes (stop/start/change with reasons, each with source_note and documented_date); draft_discharge_meds. Rules: base/references/discharge-rules.md.

Steps

  1. Run the med_reconcile engine tool (python3 base/scripts/med_reconcile.py --question <payload> --out <payload>) to compute expected_discharge_meds from admission_meds + inpatient_changes.
  2. Diff draft_discharge_meds against expected_discharge_meds in both directions - additions and omissions.
  3. Record every discrepancy with its type, its numbered rule citation and the documenting note/date it came from.
  4. Set clean only when the discrepancy list is empty and no inpatient action was unrecognised; raise one escalation per discrepancy.
  5. Hand reconciliation_report to summary-draft and patient-instructions; never re-derive the list downstream.

Output

reconciliation_report on the contract: {expected_discharge_meds[{drug, dose, status, reason, source_note, documented_date}], stopped_meds[{drug, status, reason, source_note, documented_date}], discrepancies[{drug, type, detail, citation, source_note, documented_date}], clean, source} plus one escalation string per discrepancy. expected_discharge_meds lists only medications expected to be active at discharge; reason is present only when an inpatient start or change set it. A medication stopped in-house is not on that list - it is on stopped_meds with its stop reason and citation (so summary-draft can show the discontinuation), and it surfaces as a discrepancy if the draft mishandles it. unrecognised_actions[] appears only when an inpatient change has an action other than start/stop/change. Seven discrepancy types, each mirroring a numbered rule:

  • unresolved_stop_reappeared (#1) - a stopped drug carried forward without a new order.
  • missing_from_discharge (#4) - an expected active drug absent from the draft, or listed there with a stop status that no inpatient order supports.
  • stopped_med_undocumented (#5) - a stopped drug deleted from the draft instead of listed as stopped, or listed with a stop status but no stop reason (1.0.3).
  • unordered_addition (#6) - a drug on the draft that was never on admission and never started in-house.
  • dose_mismatch (#7) - draft dose different from the expected dose.
  • change_to_absent_med (#8) - a documented change naming a drug that is not on the expected list.
  • change_provenance_missing (#9) - an inpatient change with no documenting note and date.

Read the full file on GitHub · 82 lines

Files

What ships with it

5 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.

Changes

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.

  1. 2d ago First seen · 82 lines · 134 tokens per session scan A 6862e5a2ee4f

Subscribe to this mod's changes

med-reconcile is a skill published in the GitHub repository microsoft/cat-agent-skills (101 stars, last pushed yesterday), licensed MIT. It adds 134 tokens to every session and 1,562 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-11-06.

Related

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med-reconcile next to 6 skills from other repositories
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