The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2).
Installs into .claude/skills of the current project.
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---
name: full-equity-research
description: "The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2)."
role: orchestrator
market_data_stage: none
---
# full-equity-research
```yaml
scenario: full-equity-research
stages:
- skill: business-model
- skill: competitive
- skill: recent-quarter
- skill: valuation-methods
- skill: dcf
notes: >-
Foreign issuers use 20-F/6-K instead of 10-K/8-K; small caps may skip dcf.
Dispatch each stage as its own subagent (context isolation, Q2); handoff
passes artifact PATHS, never content (Q13 rule 3).
```
Validated by `validate_scenes.py`: registry-key references + acyclicity.
