abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Map candidate research fields or subfields, their maturity, competition, entry barriers, and opportunity structure. Evidence/tool acquisition is host-selected.
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill map-research-landscape --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/map-research-landscapeContext preview
The summary Claude sees to decide when to auto-load this skill.
Map candidate research fields or subfields, their maturity, competition, entry barriers, and opportunity structure. Evidence/tool acquisition is host-selected.
name: map-research-landscape description: "Map candidate research fields or subfields, their maturity, competition, entry barriers, and opportunity structure. Evidence/tool acquisition is host-selected."
Map candidate research fields or subfields, maturity, competition, entry barriers, tractability, and opportunity structure.
required: [research_intent, scope_anchor] optional: [actor_profile, seed_evidence, constraints] constraints: [candidate fields require evidence references and declared comparison dimensions]
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
1. You MUST load skill `generate-candidate-directions` to generate diverse candidate fields and deliberate boundary crossings. 2. You MUST load skill `synthesize-field-panorama` to synthesize maturity, competition, entry-barrier, tractability, and opportunity evidence. If the resulting fields must be ordered, screened, or selected under explicit criteria, consider `rank-candidates` as the next tactic.
Deviation: Evidence acquisition is host-selected; do not invoke removed tool wrappers. Re-run candidate generation only when intent or scope changes materially.
produces: [candidate_field_set, field_panorama, maturity_map, competition_map, opportunity_structure] delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
Reject niche lists with no evidence, maturity claims based on publication volume alone, and opportunity claims that omit competition or entry barriers.
| source | source line | kind | source criterion | |---|---:|---|---| | none retained | - | - | No source numeric/textual criterion retained after normalization. |
Append candidate fields, evidence references, dimension assessments, boundary-crossing rationale, and unresolved acquisition questions.
The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.
Repo: yogsoth-ai/de-anthropocentric-research-engine
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Evaluate competing arguments against stated criteria and produce a reasoned verdict with uncertainty.
Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context, outcome, timeframe, system…
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. Perspective, target, escalation depth,…
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.