clinical-trial-protocol-waypoint-based-design

Sub-skill of clinical-trial-protocol: Waypoint-Based Design (+2).

5 stars

Best use case

clinical-trial-protocol-waypoint-based-design is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of clinical-trial-protocol: Waypoint-Based Design (+2).

Teams using clinical-trial-protocol-waypoint-based-design should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/waypoint-based-design/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/science/bio-research/clinical-trial-protocol/waypoint-based-design/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/waypoint-based-design/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How clinical-trial-protocol-waypoint-based-design Compares

Feature / Agentclinical-trial-protocol-waypoint-based-designStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Sub-skill of clinical-trial-protocol: Waypoint-Based Design (+2).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Waypoint-Based Design (+2)

## Waypoint-Based Design


All analysis data is stored in `waypoints/` directory as JSON/markdown files:

```
waypoints/
├── intervention_metadata.json           # Intervention info, status, initial context
├── 01_clinical_research_summary.json   # Similar trials, FDA guidance, recommendations
├── 02_protocol_foundation.md            # Protocol sections 1-6 (Step 2)
├── 03_protocol_intervention.md          # Protocol sections 7-8 (Step 3)
├── 04_protocol_operations.md            # Protocol sections 9-12 (Step 4)
├── 02_protocol_draft.md                 # Complete protocol (concatenated in Step 4)
├── 02_protocol_metadata.json            # Protocol metadata
└── 02_sample_size_calculation.json      # Statistical sample size calculation
```

**Rich Initial Context Support:**
Users can provide substantial documentation, technical specifications, or research data when initializing the intervention (Step 0). This is preserved in `intervention_metadata.json` under the `initial_context` field. Later steps reference this context for more informed protocol development.


## Modular Subskill Steps


Each step is an independent skill in `references/` directory:

```
references/
├── 00-initialize-intervention.md    # Collect device or drug information
├── 01-research-protocols.md         # Clinical trials research and FDA guidance
├── 02-protocol-foundation.md        # Protocol sections 1-6 (foundation, design, population)
├── 03-protocol-intervention.md      # Protocol sections 7-8 (intervention details)
├── 04-protocol-operations.md        # Protocol sections 9-12 (assessments, statistics, operations)
└── 05-generate-document.md          # NIH Protocol generation
```


## Utility Scripts


```
scripts/
└── sample_size_calculator.py   # Statistical power analysis (validated)
```

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