yogsoth-ai/north-star-crystallization

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Evaluate each candidate research field on maturity, competition, entry barrier, and publication opportunity. Synthesizes broad-web-search results into a structured FieldPanorama. Must consider both niche approaches AND direct frontal competition in hot fields.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Goal-Driven Requirement Refinement Engine for Research. Crystallize a user's fuzzy research intent into a North Star statement and structured ResearchBrief through adaptive dialogue and on-demand investigation.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

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.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

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.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Present the field panorama to the user and gather their preferences — which fields interest them, which they reject, and why. A dialogue SOP that bridges landscape-synthesis output to user decision.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Analyze sub-directions within the user's chosen field and present ranked candidates. Combines sub-direction identification, skill-gap matching, and presentation into a single SOP. Depth scales by start mode: cold-start shows broad sub-directions, warm-start shows specific sub-problems, hot-start shows granular…

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Propose concrete mitigation strategies for severe obstacles. MUST use search tools to validate that proposed mitigations are realistic — no armchair theorizing. Each mitigation must have evidence of feasibility.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Quality check on leaf nodes of the GoalTree. Verify each leaf is specific enough, actionable, and that the set of leaves fully covers the top goal. Flag issues for further decomposition.

yogsoth-ai/north-star-crystallization

Skill Claude CodeCodex

Simplified crystallization strategy for users who have a general research direction (e.g., "I'm interested in LLM reasoning") but lack specificity. Simplifies actor profiling and landscape reconnaissance, then proceeds through direction narrowing, obstacle analysis, goal decomposition, and north-star synthesis. Use…