agentleFS
yogsoth-aiyogsoth-ai/north-star-crystallization/skills/cold-start/SKILL.md

cold-start

Skill2 starsChanged 6 months agoApache-2.0View on GitHub

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.

6 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 9 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 9

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    All SOPs in this strategy follow these rules:

    line 12
  2. Distinctive:

    Prefer multiple choice when possible — easier to answer

    line 15
  3. Distinctive:

    Always allow "unsure" / "TBD" as legitimate answers

    line 16
  4. Distinctive:

    Always ask WHY — not just "what do you want" but "why do you want it"

    line 17
  5. Distinctive:

    After user answers: confirm understanding before continuing

    line 18
  6. Distinctive:

    If user's answer reveals new information: immediately follow up

    line 19
  7. Distinctive:

    If user declines to answer (privacy): accept, note that downstream work becomes broader/more iterative

    line 20
  8. Distinctive:

    When to iterate and where to return to

    line 58
  9. Distinctive:

    When enough information exists to move forward

    line 59

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

TacticPurpose
actor-profilingUnderstand who the user is
landscape-reconnaissanceBroad, shallow field exploration
direction-narrowingFocus within chosen field(s)
obstacle-analysisIdentify and mitigate barriers
goal-decompositionKAOS-style AND/OR goal structuring
north-star-synthesisConverge 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.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.