---
name: agentii-ai-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)."
license: "Apache-2.0"
metadata:
  decimalai-skill-id: "f478e72d-255b-4973-9c49-a97248519109"
  decimalai-version-id: "347bd70d-282a-4832-aeb0-0d0c6ce70f7e"
  decimalai-version: "1"
  decimalai-body-sha256: "7e1e2ef899330e36d2393d8b60c2439273531ac0d673fc5dcbb99466eddd6b78"
  decimalai-name: "agentii-ai/full-equity-research"
  decimalai-format: "1"
  decimalai-invocation: "model"
  decimalai-category: "finance"
  decimalai-source: "https://app.decimal.ai/s/agentii-ai-full-equity-research@1/SKILL.md"
---
# 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.