scientific-problem-selection-reference-materials

Sub-skill of scientific-problem-selection: Reference Materials.

5 stars

Best use case

scientific-problem-selection-reference-materials is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Sub-skill of scientific-problem-selection: Reference Materials.

Teams using scientific-problem-selection-reference-materials 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/reference-materials/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/_archive/science/bio-research/scientific-problem-selection/reference-materials/SKILL.md"

Manual Installation

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

How scientific-problem-selection-reference-materials Compares

Feature / Agentscientific-problem-selection-reference-materialsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Sub-skill of scientific-problem-selection: Reference Materials.

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

# Reference Materials

## Reference Materials


Detailed skill documentation is available in the `references/` folder:

| File | Content | Search Patterns |
|------|---------|-----------------|
| `01-intuition-pumps.md` | Generate research ideas | `Intuition Pump #`, `Trap #`, `Phase [0-9]` |
| `02-risk-assessment.md` | Risk identification | `Risk.*1-5`, `go/no-go`, `assumption` |
| `03-optimization-function.md` | Success metrics | `Generality.*Learning`, `optimization`, `impact` |
| `04-parameter-strategy.md` | Parameter fixation | `fixed.*float`, `constraint`, `parameter` |
| `05-decision-tree.md` | Decision tree navigation | `altitude`, `Level [0-9]`, `decision` |
| `06-adversity-planning.md` | Adversity response | `adversity`, `crisis`, `ensemble` |
| `07-problem-inversion.md` | Problem inversion strategies | `Strategy [0-9]`, `inversion`, `goal` |
| `08-integration-synthesis.md` | Integration and synthesis | `narrative`, `communication`, `story` |
| `09-meta-framework.md` | Complete workflow | `Phase`, `workflow`, `orchestrat` |

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