Mechanism Flowchart

---

name: mechanism-flowchart

description: Generates Mermaid flowchart code and visual diagrams for pathophysiological.

license: MIT

skill-author: AIPOCH

---

# Mechanism Flowchart

Generates Mermaid flowchart code and visual representations of medical mechanisms, pathophysiology, and drug action pathways.

When to Use

Key Features

See `## Features` above for related details.

Dependencies

See `## Prerequisites` above for related details.

Example Usage

from mechanism_flowchart import MechanismDiagram

diagram = MechanismDiagram()
result = diagram.generate(
    "Type 2 Diabetes: Insulin resistance leads to hyperglycemia, "
    "causing beta cell dysfunction and further glucose elevation"
)
print(result['mermaid_code'])

Implementation Details

See `## Workflow` above for related details.

Quick Check

Use this command to verify that the packaged script entry point can be parsed before deeper execution.

python -m py_compile scripts/main.py

Audit-Ready Commands

Use these concrete commands for validation. They are intentionally self-contained and avoid placeholder paths.

python -m py_compile scripts/main.py
python scripts/main.py

Workflow

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work.

2. Validate that the request matches the documented scope and stop early if the task would require unsupported assumptions.

3. Use the packaged script path or the documented reasoning path with only the inputs that are actually available.

4. Return a structured result that separates assumptions, deliverables, risks, and unresolved items.

5. If execution fails or inputs are incomplete, switch to the fallback path and state exactly what blocked full completion.

Features

Use Cases

Input Parameters

| Parameter | Type | Required | Description |

|-----------|------|----------|-------------|

| `mechanism_description` | str | Yes | Text description of the mechanism |

| `diagram_type` | str | No | Type: "flowchart", "sequence", "state" (default: "flowchart") |

| `direction` | str | No | Flow direction: "TB", "LR", "RL", "BT" |

| `style` | str | No | Visual style: "default", "medical", "minimal" |

Output Format

{
  "mermaid_code": "string",
  "diagram_type": "string",
  "nodes": ["string"],
  "edges": ["string"],
  "rendered_svg": "string (optional)"
}

Sample Output

flowchart TB
    A[Insulin Resistance] --> B[Hyperglycemia]
    B --> C[Beta Cell Dysfunction]
    C --> D[Worsening Glucose Control]
    B --> D

Limitations

Risk Assessment

| Risk Indicator | Assessment | Level |

|----------------|------------|-------|

| Code Execution | Python/R scripts executed locally | Medium |

| Network Access | No external API calls | Low |

| File System Access | Read input files, write output files | Medium |

| Instruction Tampering | Standard prompt guidelines | Low |

| Data Exposure | Output files saved to workspace | Low |

Security Checklist

Prerequisites

# Python dependencies
pip install -r requirements.txt

Evaluation Criteria

Success Metrics

Test Cases

1. **Basic Functionality**: Standard input → Expected output

2. **Edge Case**: Invalid input → Graceful error handling

3. **Performance**: Large dataset → Acceptable processing time

Lifecycle Status

- Performance optimization

- Additional feature support

Output Requirements

Every final response should make these items explicit when they are relevant:

Error Handling

Input Validation

This skill accepts requests that match the documented purpose of `mechanism-flowchart` and include enough context to complete the workflow safely.

Do not continue the workflow when the request is out of scope, missing a critical input, or would require unsupported assumptions. Instead respond:

> `mechanism-flowchart` only handles its documented workflow. Please provide the missing required inputs or switch to a more suitable skill.

Response Template

Use the following fixed structure for non-trivial requests:

1. Objective

2. Inputs Received

3. Assumptions

4. Workflow

5. Deliverable

6. Risks and Limits

7. Next Checks

If the request is simple, you may compress the structure, but still keep assumptions and limits explicit when they affect correctness.