obstacle-analysis
$
npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/obstacle-analysisIdentify barriers, assess severity, propose mitigations, get acceptance.
SKILL.md
.github/skills/obstacle-analysisView on GitHub ↗
---
name: obstacle-analysis
description: 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.
---
# Obstacle Analysis
Identify barriers, assess severity, propose mitigations, get acceptance.
## Available SOPs
| SOP | Purpose | Execution |
|-----|---------|-----------|
| identify-obstacles | Identify obstacles from ActorProfile + chosen direction | subagent (search optional) |
| assess-obstacle-severity | Rate severity of each obstacle | subagent (search optional) |
| propose-mitigations | Propose evidence-backed mitigations | subagent (search **required**) |
| ask-obstacle-acceptance | Present obstacles + mitigations, get user decision | dialogue (search optional) |
## Search Tools Available (for all SOPs)
- web-search (web-browsing): Quick web scanning, snippets
- web-research (web-browsing): Full page reading + analysis
- literature-overview (literature-engine): Paper landscape scan
- literature-search (literature-engine): Medium-depth paper search (AI summaries)
- literature-research (literature-engine): Deep paper reading (raw full text + PDF queries)
## Methodology Guidance
- SOPs can iterate within this tactic (re-assess after new information)
- You decide whether additional search is needed to evaluate obstacles
## Hard Constraint
- Maximum 2 rounds of the full identify → assess → propose → ask cycle
- After 2 rounds of `ask-obstacle-acceptance` with unresolved obstacles: return to `present-candidates` (direction-narrowing tactic)
## Output (Tactic-Level Aggregation)
`ObstacleReport { obstacles[], mitigations[], accepted: bool }`