Transform data into insights with analysis and reporting capabilities
Version: v3.7.0 | Archetype: Analyst | Skills: 2 specialized + 15 universal
The Analyst archetype turns data into actionable insights. Unlike generic data tools, analyst agents provide:
- Pattern discovery — Identify trends, anomalies, and correlations across datasets
- Structured reporting — Generate audience-appropriate reports with metrics and visualizations
- Evidence-based conclusions — Ground insights in data, not speculation
For evaluators: If you need an AI that can analyze data methodically and communicate findings clearly to different audiences, the Analyst archetype brings analytical rigor to your workflow.
Domain knowledge that compounds: Analyst agents build persistent understanding of your data landscape — recurring patterns, baseline metrics, and reporting conventions. Unlike tools that start fresh each session, your agent accumulates analytical context that makes each analysis more focused and each report more insightful.
Analyst agents come with 2 archetype-specific skills plus the universal AGET skills.
| Skill | Description |
|---|---|
| aget-analyze-data | Analyze datasets to discover patterns, trends, and anomalies. Profiles data quality, computes statistics, and generates actionable insights. |
| aget-generate-report | Generate structured reports tailored to audience (executive, technical, operational). Includes metrics, findings, and recommendations. |
All AGET agents include session management, knowledge capture, and health monitoring:
aget-wake-up/aget-wind-down— Session lifecycleaget-create-project/aget-review-project— Project managementaget-record-lesson/aget-capture-observation— Learning captureaget-check-health/aget-check-kb/aget-check-evolution— Health monitoringaget-propose-skill/aget-create-skill— Skill developmentaget-save-state/aget-file-issue— State and issue management
Analyst agents use a formal vocabulary of 7 concepts organized into 3 clusters:
| Cluster | Concepts |
|---|---|
| Data Analysis | Dataset, Analysis, Pattern |
| Metrics | Metric, Trend, Anomaly |
| Reporting | Report |
This vocabulary enables precise communication about analytical work.
See: ontology/ONTOLOGY_analyst.yaml
# 1. Clone the template
git clone https://github.com/aget-framework/template-analyst-aget.git my-analyst-agent
cd my-analyst-agent
# 2. Configure identity
# Edit .aget/version.json:
# "agent_name": "my-analyst-agent"
# "domain": "your-domain"
# 3. Verify setup
python3 -m pytest tests/ -v
# Expected: All tests passing# In Claude Code CLI
/aget-analyze-data # Analyze a dataset
/aget-generate-report # Create a structured report| Aspect | Generic Data Tool | Analyst Agent |
|---|---|---|
| Data profiling | Schema inspection | Quality assessment with completeness scores |
| Pattern detection | Manual queries | Automated trend and anomaly identification |
| Reporting | Raw exports | Audience-tailored reports with context |
| Vocabulary | Ad-hoc | Formal ontology (Dataset, Metric, Trend) |
| Domain memory | Starts fresh each session | Accumulates analytical expertise over time |
| Attribute | Value |
|---|---|
| Framework | AGET v3.7.0 |
| Archetype | Analyst |
| Skills | 17 total (2 archetype + 15 universal) |
| Ontology | 7 concepts, 3 clusters |
| License | Apache 2.0 |
- AGET Framework — Core framework documentation
- Archetype Guide — All 12 archetypes explained
- Getting Started — Full onboarding guide
| Archetype | Best For |
|---|---|
| Researcher | Literature search and knowledge synthesis |
| Advisor | Risk assessment and recommendations |
| Developer | Code analysis and quality metrics |
AGET Framework | Apache 2.0 | Issues