| 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