Cold Start Strategy
SkillDev toolsFull crystallization strategy for users who have no research direction
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Cold Start Strategy skill
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/cold-start/SKILL.md and read by ahel’s review.
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:
- A default flow as starting reference
- Available tactics with their purposes
- 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.
Available Tactics
Optional, no fixed order; the final leaf is always a sop.
| Tactic | When to use |
|---|---|
| actor-profiling | Understand who the user is — background, resources, constraints, and deep motivations. Produces an ActorProfile that informs all downstream decisions. Use this tactic at the start of any crystallization process to build a model of the user's capabilities, limitations, and intent. |
| direction-narrowing | Focus within the user's chosen field(s). Identify specific sub-directions through deep paper and web research, then present ranked candidates. Use after landscape-reconnaissance has identified fields of interest. |
| goal-decomposition | Structure the user's chosen direction into a formal goal tree using KAOS-style AND/OR decomposition. Validate feasibility against ActorProfile and ObstacleReport. Use after obstacle-analysis confirms the direction is viable. |
| landscape-reconnaissance | Broad, shallow exploration of candidate research fields. Understand what's out there before narrowing. Use when the user needs to discover which fields are available to them — especially in cold-start and warm-start scenarios. |
| north-star-synthesis | Converge all accumulated context into a crystallized North Star statement and structured ResearchBrief. Performs self-review before presenting to user. Use as the final tactic in any start mode — this is where everything comes together. |
| obstacle-analysis | Identify what blocks the user from pursuing their chosen direction, assess severity, propose mitigations with search-validated evidence, and get user acceptance. Use after direction-narrowing has identified a specific direction. |
Signals
- GitHub stars
- 469
- Forks
- 37
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
cold-start-yogsoth-ai- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine