landscape-reconnaissance

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/landscape-reconnaissance

Explores candidate research fields to identify opportunities

  • Helps users discover available fields in cold-start or warm-start scenarios
  • Uses web search and subagent workflows to gather and synthesize data
  • Balances breadth of exploration with consideration of competition and novelty
  • Presents a synthesized overview and asks user to select 1-2 fields of interest

SKILL.md

.github/skills/landscape-reconnaissanceView on GitHub ↗
---
name: landscape-reconnaissance
description: 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.
---

# Landscape Reconnaissance

Broad, shallow field exploration. Understand the landscape of possibilities before narrowing.

## Available SOPs

| SOP | Purpose | Execution |
|-----|---------|-----------|
| generate-candidate-fields | Generate candidate fields from ActorProfile | subagent |
| broad-web-search | Scan web for each candidate field | import: web-search |
| landscape-synthesis | Synthesize search results into FieldPanorama | subagent |
| present-and-ask | Present panorama to user, get field selection | dialogue |

## Methodology Guidance

- If iteration is needed, expand breadth (more fields, more searches), never depth
- Depth is direction-narrowing's job
- You decide when enough information exists to synthesize

## Hard Constraints

- `broad-web-search`: brave_web_search count=10 per call, at least 150 total results before synthesis
- `landscape-synthesis`: Don't only chase niche/novel combinations. Must also consider direct frontal competition in hot fields. The ambition to tackle hard problems head-on must be present.

## Output (Tactic-Level Aggregation)

`FieldPanorama[] + user's selected 1-2 fields of interest`

More from yogsoth-ai/de-anthropocentric-research-engine