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Cold Start

ASecurity

Full crystallization strategy for users who have no research direction at all. Covers actor profiling, landscape reconnaissance, direction narrowing, obstacle analysis, goal decomposition, and north-star synthesis. Use when the user's first message reveals zero specificity about what they want to research.

417 stars
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Added 6/1/2026
researchgogit

Works with

cli

Security Analysis

A100/100

Scanned 6/1/2026

Install to Claude Code

$npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill cold-start --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.md
---
name: cold-start
description: Full crystallization strategy for users who have no research direction at all. Covers actor profiling, landscape reconnaissance, direction narrowing, obstacle analysis, goal decomposition, and north-star synthesis. Use when the user's first message reveals zero specificity about what they want to research.
---

# Cold Start Strategy

The user knows nothing — they want to publish at a top venue but have no idea what to research.

## Questioning Protocol

All SOPs in this strategy follow these rules:

- One question at a time — never overwhelm with multiple questions
- Prefer multiple choice when possible — easier to answer
- Always allow "unsure" / "TBD" as legitimate answers
- Always ask WHY — not just "what do you want" but "why do you want it"
- After user answers: confirm understanding before continuing
- If user's answer reveals new information: immediately follow up
- If user declines to answer (privacy): accept, note that downstream work becomes broader/more iterative

## Available Tactics

| Tactic | Purpose |
|--------|---------|
| actor-profiling | Understand who the user is |
| landscape-reconnaissance | Broad, shallow field exploration |
| direction-narrowing | Focus within chosen field(s) |
| obstacle-analysis | Identify and mitigate barriers |
| goal-decomposition | KAOS-style AND/OR goal structuring |
| north-star-synthesis | Converge into North Star + ResearchBrief |

## Default Flow (reference only)

```
actor-profiling → landscape-reconnaissance → direction-narrowing
→ obstacle-analysis → goal-decomposition → north-star-synthesis
```

This is a reference, not a mandate. You decide the actual execution path.

## Iteration Points

- From obstacle-analysis: may return to landscape-reconnaissance, direction-narrowing, or obstacle-analysis itself
- From goal-decomposition: may return to landscape-reconnaissance, direction-narrowing, obstacle-analysis, or goal-decomposition itself

## How to Use This Strategy

You are the general. This strategy gives you:
1. A default flow as starting reference
2. Available tactics with their purposes
3. Iteration points where backtracking makes sense

What you decide:
- Whether to execute a tactic fully or partially
- Whether to skip a tactic entirely
- Whether to invoke individual SOPs directly (bypassing tactic framing)
- When to iterate and where to return to
- When enough information exists to move forward

The only non-negotiable: the process ends with north-star-synthesis producing a North Star + ResearchBrief that the user confirms.

Attribution

yogsoth-aiyogsoth-ai
View sourceMore from yogsoth-ai →
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3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

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