Treatment Plans logo

Treatment Plans

OrganizationPopular
K-Dense-AI
treatment-plans

Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.

Overview

PublisherK-Dense-AI
Repositoryclaude-scientific-writer
Skill nametreatment-plans
Stars
2.4K
Forks
273
Bundled files
21
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 21 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by K-Dense-AI on GitHub. Read the source before you install it.

Installation

Install the Treatment Plans AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/K-Dense-AI/claude-scientific-writer.git /tmp/claude-scientific-writer
mkdir -p .claude/skills
cp -r /tmp/claude-scientific-writer/skills/treatment-plans .claude/skills/treatment-plans
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Treatment Plans in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Treatment Plans on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Treatment Plans is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Treatment-Plan Documentation

Hard safety boundary

This skill only formats and validates documentation of decisions already made, supplied, and verified by authorized licensed professionals.

Never use it to:

  • diagnose, assess, classify, or screen a person;
  • select, rank, recommend, substitute, or compare therapies;
  • choose a medication, dose, route, frequency, duration, or monitoring threshold;
  • start, stop, hold, resume, titrate, taper, or deprescribe anything;
  • check interactions, allergies, contraindications, organ-function suitability, or treatment eligibility;
  • infer missing clinical content, intervals, dates, targets, escalation criteria, or instructions;
  • triage, determine urgency, provide emergency advice, or create a safety plan;
  • predict outcomes, prognosis, response, benefit, harm, or clinical appropriateness;
  • replace medication reconciliation, pharmacist review, informed consent, clinician review, or an authorized clinical system;
  • claim FDA approval, HIPAA compliance, legal compliance, completeness of care, clinical safety, or standard-of-care conformity.

If a request crosses a boundary, stop. Ask for a locally verified clinician-authored record or route the matter to the responsible licensed professional. Do not redirect to another skill to obtain a patient-specific recommendation.

If a concern may be urgent or emergent, stop this workflow and route it through the institution's current clinical escalation or emergency process. This skill does not decide urgency and does not provide emergency instructions.

Required visible notice

Every component and derived schedule must display:

DRAFT — NOT MEDICAL ADVICE — DOCUMENTATION-ONLY — AUTHORIZED CLINICIAN SIGN-OFF REQUIRED

Structural success never removes this notice. Only the authorized local workflow may set the release gate.

Data gate

Prefer synthetic or qualified de-identified structured manifests. Do not place patient names, medical-record numbers, contact details, dates of birth, addresses, free-text notes, images, or other direct identifiers in examples.

For any real-patient or patient-derived data:

  1. Work only in a locally authorized environment under the institution's current privacy, security, retention, and access policies.
  2. Use the minimum information necessary for the documented purpose, even when a legal exception may apply.
  3. Do not send content to a model, search engine, API, image service, telemetry service, or any other external tool.
  4. Do not copy content into chat prompts, command history, logs, test fixtures, examples, screenshots, or reports.
  5. Run bundled scripts only against local paths. Their reports identify rule codes and field paths, not clinical values.
  6. Require qualified privacy review before treating patient-derived material as de-identified or releasing it.

If these conditions are not documented, do not read or process the content. Use synthetic templates only.

Allowed inputs

Accept only bounded UTF-8 JSON objects built from these generic templates:

  • assets/source_fact_manifest_template.json
  • assets/clinician_authored_intervention_template.json
  • assets/goals_monitoring_checkpoint_template.json
  • assets/informed_preference_shared_decision_template.json
  • assets/transition_reconciliation_template.json
  • assets/intended_use_handoff_template.json

The templates contain no disease-specific recommendations, example patients, clinical intervals, doses, targets, thresholds, or inferred care pathways. Empty template arrays and pending attestations are intentional release blockers.

Workflow

1. Establish authority and intended use

  • Confirm the accountable clinical owner and authorized licensed signatory.
  • Confirm that every clinical decision already exists in a verified local source.
  • Record jurisdiction, institution, setting, document owner, local policies, retention rule, and intended recipients.
  • Record whether the package is synthetic, qualified de-identified, or real-patient minimum-necessary data.
  • Keep the release gate blocked until every required review is complete.

Read references/safety_scope.md and references/privacy_governance.md before processing patient-derived material.

2. Generate a generic package

bash
python3 scripts/generate_template.py \
  --output-dir ./local-plan-package \
  --subject-ref SYNTHETIC-CASE-001 \
  --classification synthetic

The generator copies all six templates. It does not create clinical content and does not overwrite existing files.

3. Transcribe supplied decisions without inference

  • Copy only clinician-authored facts and interventions from verified local sources.
  • Preserve source locators, versions/dates, author role, verification role, and verification time.
  • Record goals, monitoring items, checkpoint dates, and transition dates exactly as supplied.
  • Record options, benefits, harms, uncertainty, preferences, and the outcome only as documented by the responsible clinician.
  • Leave missing fields unresolved. Never fill them from general knowledge.
  • For medication content, record the clinician-authored text and current local source references; do not interpret or validate it.

See references/documentation_workflow.md, references/source_boundaries.md, and references/shared_decision_handoff.md.

4. Run deterministic local checks

From the skill directory:

bash
python3 scripts/validate_treatment_plan.py ./local-plan-package
python3 scripts/validate_traceability.py ./local-plan-package
python3 scripts/check_completeness.py ./local-plan-package
python3 scripts/privacy_process_check.py ./local-plan-package
python3 scripts/check_consistency.py ./local-plan-package
python3 scripts/timeline_generator.py ./local-plan-package \
  --output ./local-plan-package/explicit-date-schedule.json

The scripts:

  • reject non-local paths, symlinks, duplicate JSON keys, unknown fields, oversized inputs, excessive nesting, and unbounded collections;
  • never use network access, environment variables, dynamic execution, pickle, subprocesses, images, or LLMs;
  • never assess diagnosis, medication safety, interactions, contraindications, clinical appropriateness, urgency, prognosis, or guideline concordance;
  • schedule only dates already supplied in the package and never derive recurrence or clinical intervals;
  • minimize reports to counts, rule codes, document types, and field paths.

5. Human review and release

Require the accountable authorized team to:

  • compare every transcribed item with its signed source;
  • perform medication reconciliation and all clinical checks in approved systems;
  • verify current FDA labeling, Medication Guide, REMS materials, and local formulary/policy when applicable;
  • resolve every discrepancy and missing item;
  • review shared-decision and informed-preference documentation;
  • review transition recipients, ownership, pending results, and local escalation routing;
  • complete privacy, security, legal, regulatory, records, and institutional review as applicable;
  • sign, date, and release through the authorized record system.

The final handoff must retain provenance and unresolved-item routing. A script pass is not authorization to use the package for care.

Source boundaries

  • Use FDA labeling databases, current Medication Guides, and REMS materials as authoritative source records only when an authorized clinician or pharmacist verifies applicability. This skill does not interpret them.
  • Use WHO or Joint Commission transition guidance only for process structure such as information transfer, reconciliation documentation, ownership, and checklists.
  • Use AHRQ, NICE, or applicable professional guidance to document that shared decision-making occurred; do not generate options or risk estimates.
  • Apply CMS documentation requirements only when the exact program, provider type, jurisdiction, and current local policy are confirmed.
  • Route safety events, product reports, privacy incidents, and other reportable matters through current local governance. This skill records a route; it does not submit reports.

See references/source_ledger.md for the dated official-source ledger.

Verification

bash
PYTHONDONTWRITEBYTECODE=1 python3 -m unittest discover \
  -s tests/treatment-plans -p 'test_*.py' -v

Run AST parsing without bytecode:

bash
PYTHONDONTWRITEBYTECODE=1 python3 -c \
  "import ast,pathlib; [ast.parse(p.read_text()) for p in pathlib.Path('scripts').glob('*.py')]"

Reference map

  • references/README.md — scope and navigation
  • references/safety_scope.md — refusal, routing, and release boundaries
  • references/privacy_governance.md — local handling and de-identification limits
  • references/documentation_workflow.md — package lifecycle and review gates
  • references/source_boundaries.md — FDA labeling, REMS, and governance boundaries
  • references/shared_decision_handoff.md — informed preferences, reconciliation, and transitions
  • references/source_ledger.md — dated authoritative sources
  • references/security_validation.md — baseline findings and validation record

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Treatment Plans AI skill do?

Format and structurally validate local treatment-plan documentation after clinical decisions have already been supplied and verified by authorized licensed professionals. Use for source traceability, clinician-authored intervention records, goals and checkpoints, shared-decision records, reconciliation handoffs, and release gates—not for clinical decision-making.

Why use Treatment Plans on TypingMind?

Because you install it once and use it with any model. Treatment Plans is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Treatment Plans in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/K-Dense-AI/claude-scientific-writer/tree/main/skills/treatment-plans. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Treatment Plans?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Treatment Plans?

As many as you like. As long as a model supports skills, you can use Treatment Plans with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Treatment Plans AI skill free?

Yes. It is published on GitHub by K-Dense-AI under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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