Best use case
research-provenance is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
It is a strong fit for teams already working in Codex.
Query provenance chains and artifact relationships
Teams using research-provenance should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-provenance/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-provenance Compares
| Feature / Agent | research-provenance | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Query provenance chains and artifact relationships
Which AI agents support this skill?
This skill is designed for Codex.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
AI Agents for Startups
Explore AI agent skills for startup validation, product research, growth experiments, documentation, and fast execution with small teams.
AI Agent for YouTube Script Writing
Find AI agent skills for YouTube script writing, video research, content outlining, and repeatable channel production workflows.
AI Agent for Product Research
Browse AI agent skills for product research, competitive analysis, customer discovery, and structured product decision support.
SKILL.md Source
# Research Provenance Command
Query W3C PROV-compliant provenance chains to trace artifact derivations and relationships.
## Instructions
When invoked, perform provenance queries:
1. **Load Provenance Records**
- If REF-XXX, load all provenance records for that paper
- If artifact path, load records for that specific artifact
- Build provenance graph from PROV relationships
2. **Execute Query**
- Query types:
- `what-derives` - What artifacts derive from this source?
- `what-cites` - What documents cite this source?
- `history` - Full derivation history of this artifact
- `lineage` - Complete lineage from source to current state
- `impact` - Impact analysis (what would be affected by changes?)
3. **Traverse Graph**
- Follow `wasDerivedFrom` relationships
- Follow `wasGeneratedBy` activities
- Follow `wasAssociatedWith` agents
- Collect all related entities, activities, and agents
4. **Format Results**
- Visualize as tree, graph, or table
- Show derivation chains
- Highlight gaps or inconsistencies
- Calculate impact metrics
5. **Report**
- Display provenance chain
- Show relationship types
- Include timestamps and agents
- Flag any provenance issues
## Arguments
- `[ref-id or path]` - Source identifier or artifact path (required)
- `--query [what-derives|what-cites|history|lineage|impact]` - Query type (default: what-derives)
- `--depth [n]` - Maximum graph traversal depth (default: 5)
- `--output [tree|graph|table|json]` - Output format (default: tree)
- `--validate` - Validate provenance chain integrity
- `--export-dot` - Export as GraphViz DOT format
## Examples
```bash
# Find what derives from a paper
/research-provenance REF-022 --query what-derives
# Find citation usage
/research-provenance REF-022 --query what-cites
# Get full history of an artifact
/research-provenance .aiwg/architecture/agent-orchestration-sad.md --query history
# Analyze impact of changes
/research-provenance REF-022 --query impact --depth 10
# Validate provenance chain
/research-provenance REF-022 --validate
# Export as graph
/research-provenance REF-022 --query lineage --export-dot
```
## Expected Output
### What Derives Query
```
/research-provenance REF-022 --query what-derives
Provenance Query: REF-022 - What Derives From This Source?
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Source: REF-022 (AutoGen: Enabling Next-Gen LLM Applications...)
Derivation Tree:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
REF-022.pdf (source paper)
│
├─→ REF-022-autogen.md (finding document)
│ │ Relationship: wasDerivedFrom
│ │ Activity: documentation
│ │ Agent: documentation-agent
│ │ Date: 2026-02-03T12:15:00Z
│ │
│ ├─→ REF-022-notes.md (literature notes)
│ │ Relationship: wasDerivedFrom
│ │ Activity: synthesis
│ │ Agent: documentation-agent
│ │ Date: 2026-02-03T12:20:00Z
│ │
│ └─→ UC-174-conversable-agent.md (use case)
│ Relationship: wasInformedBy
│ Activity: requirements_analysis
│ Agent: requirements-analyst
│ Date: 2026-02-03T13:00:00Z
│
├─→ REF-022-assessment.yaml (quality assessment)
│ Relationship: wasDerivedFrom
│ Activity: quality_assessment
│ Agent: quality-agent
│ Date: 2026-02-03T12:30:00Z
│
└─→ .claude/rules/conversable-agent-interface.md (implementation rule)
Relationship: wasInformedBy
Activity: rule_creation
Agent: architect
Date: 2026-02-03T14:00:00Z
Summary:
Total derived artifacts: 5
Derivation depth: 2 levels
Agents involved: 4 (documentation-agent, quality-agent, requirements-analyst, architect)
Time span: 2026-02-03 12:15 - 14:00 (1h 45m)
```
### What Cites Query
```
/research-provenance REF-022 --query what-cites
Provenance Query: REF-022 - Citation Usage
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Source: REF-022 (AutoGen: Enabling Next-Gen LLM Applications...)
Citation Map:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Documents citing REF-022:
1. .aiwg/architecture/agent-orchestration-sad.md
Lines: 78, 142, 267
Context: Multi-agent conversation patterns
Quality compliance: ✓ APPROPRIATE (MODERATE hedging for LOW evidence)
2. .aiwg/requirements/use-cases/UC-174-conversable-agent.md
Lines: 23, 45
Context: Conversable agent interface design
Quality compliance: ✓ APPROPRIATE
3. .claude/rules/conversable-agent-interface.md
Lines: 12, 89
Context: Research foundation for agent protocol
Quality compliance: ✓ APPROPRIATE
4. .claude/rules/auto-reply-chains.md
Lines: 15, 34, 67
Context: Auto-reply pattern implementation
Quality compliance: ✓ APPROPRIATE
5. docs/agent-framework.md
Lines: 78
Context: Agent capabilities overview
Quality compliance: ✗ VIOLATION - "Research demonstrates" too strong for LOW evidence
Suggestion: Change to "Limited evidence suggests"
6. .aiwg/architecture/adr-012-agent-protocol.md
Lines: 45
Context: Protocol design rationale
Quality compliance: ✗ VIOLATION - "Studies prove" too strong
Suggestion: Change to "Preliminary findings indicate"
Summary:
Total citations: 12 (across 6 documents)
Compliant citations: 10 (83%)
Policy violations: 2 (17%)
Remediation needed: docs/agent-framework.md, .aiwg/architecture/adr-012-agent-protocol.md
```
### History Query
```
/research-provenance .aiwg/architecture/agent-orchestration-sad.md --query history
Provenance Query: agent-orchestration-sad.md - Derivation History
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Artifact: .aiwg/architecture/agent-orchestration-sad.md
Derivation History (chronological):
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
2026-01-15T10:00:00Z - CREATION
Activity: initial_architecture_design
Agent: architect
Based on:
- .aiwg/requirements/use-cases/UC-001-orchestrator.md
- .aiwg/intake/solution-profile.md
2026-01-20T14:30:00Z - REFINEMENT
Activity: architecture_refinement
Agent: architect
Informed by:
- REF-001-production-agentic.md (best practices)
- Technical review feedback
2026-02-03T13:45:00Z - ENHANCEMENT
Activity: research_integration
Agent: architect
Integrated findings from:
- REF-022-autogen.md (conversable agent interface)
- REF-057-agent-laboratory.md (HITL patterns)
Changes:
- Added conversable agent interface section
- Enhanced HITL gate definitions
- Updated agent communication patterns
Current State:
Version: 3.0
Last modified: 2026-02-03T13:45:00Z
Size: 47 KB
Sections: 12
Referenced by: 8 artifacts
Checksum: def456...
Provenance Chain:
.aiwg/requirements/UC-001-orchestrator.md
→ .aiwg/architecture/agent-orchestration-sad.md (v1.0)
← REF-001-production-agentic.md
→ .aiwg/architecture/agent-orchestration-sad.md (v2.0)
← REF-022-autogen.md
← REF-057-agent-laboratory.md
→ .aiwg/architecture/agent-orchestration-sad.md (v3.0, current)
```
### Impact Analysis
```
/research-provenance REF-022 --query impact
Provenance Query: REF-022 - Impact Analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Source: REF-022 (AutoGen: Enabling Next-Gen LLM Applications...)
Impact Analysis: What would be affected by changes to REF-022?
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Direct Dependencies (5):
- REF-022-autogen.md (finding document) - CRITICAL
- REF-022-assessment.yaml (quality assessment) - HIGH
- REF-022-notes.md (literature notes) - MEDIUM
- UC-174-conversable-agent.md (use case) - HIGH
- .claude/rules/conversable-agent-interface.md - HIGH
Indirect Dependencies (12):
- .aiwg/architecture/agent-orchestration-sad.md
- src/agents/conversable-agent-interface.ts
- test/unit/agents/conversable-agent.test.ts
- .claude/rules/auto-reply-chains.md
- docs/agent-framework.md
... (7 more)
Citation Dependencies (12 citations across 6 documents):
- 10 citations in architecture/requirements
- 2 citations in documentation
Implementation Dependencies (3):
- src/agents/conversable-agent-interface.ts (implements patterns)
- src/orchestration/conversation-manager.ts (uses patterns)
- test/integration/multi-agent-conversation.test.ts (validates patterns)
Impact Metrics:
Total affected artifacts: 17
Critical dependencies: 1
High priority dependencies: 4
Medium priority dependencies: 3
Citation count: 12
Risk Assessment:
If REF-022 quality assessment changes from LOW to VERY LOW:
- 2 citations would become violations (overclaiming)
- 1 use case would need revision
- 1 implementation rule would need hedging update
If REF-022 findings are contradicted by new research:
- 5 artifacts would require immediate review
- 12 citations would need revalidation
- 3 implementation patterns would need reassessment
```
## Validation
When --validate is used:
```
/research-provenance REF-022 --validate
Validating Provenance Chain: REF-022
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Validation Checks:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
✓ All provenance records exist
✓ All referenced artifacts exist
✓ All agents are registered
✓ All activities have timestamps
✓ All derivation chains are complete
✓ No circular dependencies detected
✓ All checksums match fixity manifest
✗ 2 citation policy violations found
Issues:
[WARNING] Citation policy violation in docs/agent-framework.md:78
- Hedging too strong for GRADE level
- Recommendation: Update to "Limited evidence suggests"
[WARNING] Citation policy violation in .aiwg/architecture/adr-012-agent-protocol.md:45
- Hedging too strong for GRADE level
- Recommendation: Update to "Preliminary findings indicate"
Overall Status: PASS with warnings
Critical issues: 0
Warnings: 2
Info: 0
Remediation:
Run: /research-quality REF-022 --check-citations --fix
```
## GraphViz Export
Export provenance graph for visualization:
```bash
/research-provenance REF-022 --query lineage --export-dot
Output:
Provenance graph exported to: .aiwg/research/provenance/graphs/REF-022-lineage.dot
To visualize:
dot -Tpng REF-022-lineage.dot -o REF-022-lineage.png
dot -Tsvg REF-022-lineage.dot -o REF-022-lineage.svg
```
## References
- @$AIWG_ROOT/agentic/code/frameworks/research-complete/agents/provenance-agent.md - Provenance Agent
- @$AIWG_ROOT/src/research/services/provenance-service.ts - Provenance query implementation
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/schemas/provenance/prov-record.yaml - PROV schema
- @.aiwg/research/provenance/README.md - Provenance tracking
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/rules/provenance-tracking.md - Provenance requirements
- https://www.w3.org/TR/prov-dm/ - W3C PROV-DM specificationRelated Skills
Provenance Tracking
W3C PROV-O patterns for tracking media derivation chains and production history
research-workflow
Execute multi-stage research workflows
research-status
Show research corpus health and statistics
research-query
Search the local research corpus, read matching findings, and synthesize an answer with inline citations to REF-XXX sources. The "query" operation for the research pipeline.
research-quality
Assess source quality using GRADE methodology
research-quality-audit
Audit research corpus for shallow stubs, incomplete sections, missing source files, and doc depth issues. Detects docs written from abstracts rather than full papers and optionally auto-dispatches expansion agents.
research-lint
Run the research corpus lint ruleset to detect structural and referential integrity issues — orphan notes, missing frontmatter, broken references, missing GRADE assessments.
research-gap
Analyze gaps in research coverage
research-gap-detect
Build the mutual citation graph, find connected components, identify isolated clusters, and optionally search for bridge candidates and file gap issues. Automates the manual cluster analysis workflow.
research-document
Generate summaries and literature notes from research papers
research-discover
Search for research papers across academic databases
research-cite
Generate properly formatted citation from research corpus