scoping-survey

name	scoping-survey
description	Broad landscape mapping strategy — quickly understand what exists in a field. Prioritizes breadth over depth with high paper-overview volume and minimal deep reading. Use when entering a new field or needing orientation before committing to deeper investigation.

Scoping Survey

Purpose: Broad and shallow — map the landscape of a field quickly. Understand what exists, who's working on what, and where the boundaries are.

When to use: User is entering a new field, needs orientation before committing to deeper investigation.

Budget

Base SOP	Target	±10% Range
web-search	100 results	90–110
web-research	10 pages	9–11
paper-overview	100 papers	90–110
paper-search	20 papers	18–22
paper-research	0	0

CC may deviate within ±10% with documented reasoning. If the field is genuinely small (fewer papers exist), document and proceed.

State Ledger

Print this table before each major iteration decision:

| SOP            | Target | Current | % Complete |
|----------------|--------|---------|------------|
| web-search     | 100    | ???     | ???%       |
| web-research   | 10     | ???     | ???%       |
| paper-overview | 100    | ???     | ???%       |
| paper-search   | 20     | ???     | ???%       |

Do not exit the strategy until all rows reach ≥90%.

Available Tactics

None mandatory — CC composes directly from SOPs.

Available SOPs

Import (strict protocol execution):

• web-search → web-browsing/skills/web-search/SKILL.md
• web-research → web-browsing/skills/web-research/SKILL.md
• paper-overview → literature-engine/skills/literature-overview/SKILL.md
• paper-search → literature-engine/skills/literature-search/SKILL.md

Subagent (optional, CC decides):

• categorize-papers — cluster papers by theme/method/timeline
• taxonomy-mapping — construct hierarchical field map
• gap-identification — find what the literature hasn't addressed
• survey-synthesis — produce final structured output

Execution Guidance

• Prioritize breadth over depth — many queries, fast scanning
• paper-overview is the primary operation (100 papers scanned at abstract level)
• paper-search (20 papers with AI summaries) is selective — only for key papers that need slightly deeper understanding
• No paper-research — this strategy does not deep-read
• taxonomy-mapping is particularly valuable here (produces field map)
• End with survey-synthesis to produce structured output

Output Format

Field Landscape Map containing:

• Taxonomy of sub-areas (hierarchical)
• Key authors and research groups per sub-area
• Research trends (hot / active / declining / dormant)
• Open questions and unexplored directions
• Entry points for deeper investigation