Best use case
research-status 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.
Show research corpus health and statistics
Teams using research-status 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-status/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-status Compares
| Feature / Agent | research-status | Standard Approach |
|---|---|---|
| Platform Support | Codex | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Show research corpus health and statistics
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.
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SKILL.md Source
# Research Status Command
Display comprehensive health check and statistics for the research corpus.
## Scope Boundary
`corpus-health` / `research-status` is **structural** — it checks whether the corpus is well-formed:
- Are files present where expected? (orphans, missing artifacts)
- Is frontmatter complete and valid? (schema violations)
- Are references intact? (broken links, missing provenance)
- Is the data well-organized? (checksums, naming, metadata)
For **intellectual** gap analysis — what topics lack coverage, what claims lack evidence, what contradictions are unresolved — use `research-gap` instead.
For **declarative rule checking** (automated, CI-ready), use `research-lint` which runs the `research` lint ruleset.
## Instructions
When invoked, analyze corpus health:
1. **Scan Corpus**
- Count papers in `.aiwg/research/sources/`
- Count finding documents
- Count quality assessments
- Count archival packages
- Identify orphaned or incomplete artifacts
2. **Validate Integrity**
- Check fixity manifest integrity
- Verify all checksums
- Detect corrupted files
- Find missing provenance records
3. **Assess Completeness**
- Papers missing finding documents
- Papers missing quality assessments
- Papers missing archival packages
- Incomplete frontmatter
- Missing metadata fields
4. **Analyze Coverage**
- Topic distribution
- Publication year distribution
- Source type distribution (journal, conference, preprint)
- GRADE quality distribution
5. **Check Policy Compliance**
- Citation policy violations
- GRADE hedging compliance
- Provenance completeness
- Metadata standards adherence
6. **Generate Report**
- Summary statistics
- Health score
- Problem areas flagged
- Remediation suggestions
## Arguments
- `--detailed` - Show detailed statistics and breakdowns
- `--problems-only` - Only show issues requiring attention
- `--export [json|yaml|markdown]` - Export report to file
- `--validate-all` - Perform deep validation (slower, thorough)
- `--check-citations` - Include citation policy validation
## Examples
```bash
# Basic status check
/research-status
# Detailed analysis
/research-status --detailed
# Show only problems
/research-status --problems-only
# Full validation with citation check
/research-status --validate-all --check-citations
# Export report
/research-status --detailed --export markdown
```
## Expected Output
### Standard Mode
```
Research Corpus Health Check
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Corpus Statistics:
─────────────────────────────────────────────────────────────────────
Papers: 47
Finding Documents: 47 (100%)
Quality Assessments: 45 (96%)
Archival Packages: 42 (89%)
Literature Notes: 38 (81%)
Total Size: 142.8 MB
Oldest Paper: 2018
Newest Paper: 2024
Health Score: 92/100 (GOOD)
─────────────────────────────────────────────────────────────────────
Completeness:
─────────────────────────────────────────────────────────────────────
✓ All papers have finding documents
⚠ 2 papers missing quality assessments (REF-044, REF-045)
⚠ 5 papers missing archival packages (REF-041-045)
✓ Fixity manifest up to date
✓ Provenance records complete
Quality Distribution:
─────────────────────────────────────────────────────────────────────
HIGH: 12 papers (26%) ████████░░░░░░░░░░░░░░░░░░
MODERATE: 18 papers (38%) ███████████████░░░░░░░░░░░
LOW: 14 papers (30%) ████████████░░░░░░░░░░░░░░
VERY LOW: 3 papers (6%) ██░░░░░░░░░░░░░░░░░░░░░░░░
Source Types:
─────────────────────────────────────────────────────────────────────
Peer-reviewed Journal: 15 (32%)
Peer-reviewed Conference: 22 (47%)
Preprint: 8 (17%)
Technical Report: 2 (4%)
Topics (Top 5):
─────────────────────────────────────────────────────────────────────
1. agentic-workflows 24 papers
2. llm-evaluation 18 papers
3. human-in-the-loop 14 papers
4. multi-agent-systems 12 papers
5. cognitive-scaffolding 9 papers
Issues Requiring Attention:
─────────────────────────────────────────────────────────────────────
⚠ 2 papers need quality assessment:
- REF-044 (acquired 7 days ago)
- REF-045 (acquired 5 days ago)
⚠ 5 papers need archival:
- REF-041, REF-042, REF-043, REF-044, REF-045
⚠ 9 papers need literature notes
Next Steps:
─────────────────────────────────────────────────────────────────────
1. /research-quality REF-044 REF-045 - Complete quality assessments
2. /research-archive REF-041 REF-042 REF-043 REF-044 REF-045
3. /research-document REF-038 --depth comprehensive --include-notes
Last Corpus Update: 2026-02-03T14:35:25Z (15 minutes ago)
```
### Detailed Mode
```
/research-status --detailed
Research Corpus Health Check (Detailed)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Corpus Statistics:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Papers by Year:
2024: ███████████ 18 (38%)
2023: ██████████ 15 (32%)
2022: ████ 6 (13%)
2021: ███ 4 (9%)
2020: ██ 3 (6%)
2019: ░ 1 (2%)
Papers by GRADE Level:
HIGH: ████████ 12 (26%)
- Systematic Reviews: 4
- Meta-analyses: 2
- High-quality RCTs: 6
MODERATE: ███████████████ 18 (38%)
- Conference Papers: 12
- Cohort Studies: 6
LOW: ████████████ 14 (30%)
- Case Series: 8
- Limited Evaluation: 6
VERY LOW: ██ 3 (6%)
- Preprints (not peer-reviewed): 2
- Blog Posts: 1
Papers by Source:
ACM Digital Library: 12
IEEE Xplore: 8
arXiv: 15
Nature/Science: 5
Springer: 4
Other: 3
AIWG Relevance:
HIGH: 32 papers (68%) - Direct applicability
MEDIUM: 12 papers (26%) - Tangential relevance
LOW: 3 papers (6%) - Background/context only
Citation Usage:
Total citations across corpus: 347
Average citations per paper: 7.4
Most cited: REF-001 (34 citations)
Least cited: REF-044 (0 citations, new)
Completeness Matrix:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Artifact Type Count % Status
────────────────────────────────────────────────────────────────────
Source PDFs 47/47 100% ✓ Complete
Finding Documents 47/47 100% ✓ Complete
Quality Assessments 45/47 96% ⚠ 2 missing
Archival Packages 42/47 89% ⚠ 5 missing
Literature Notes 38/47 81% ⚠ 9 missing
Provenance Records 47/47 100% ✓ Complete
Metadata Completeness:
────────────────────────────────────────────────────────────────────
DOI: 44/47 94% ⚠ 3 preprints lack DOI
Authors: 47/47 100% ✓ Complete
Year: 47/47 100% ✓ Complete
Abstract: 46/47 98% ⚠ 1 missing
Keywords: 38/47 81% ⚠ 9 missing
Citation Count: 45/47 96% ⚠ 2 missing
Integrity Checks:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Fixity Validation: 47/47 100% ✓ All checksums verified
Provenance Chains: 47/47 100% ✓ Complete
Broken References: 0 ✓ None found
Orphaned Files: 0 ✓ None found
Storage Metrics:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Total Size: 142.8 MB
Source PDFs: 128.4 MB (90%)
Finding Documents: 2.1 MB (1%)
Literature Notes: 0.8 MB (1%)
Quality Assessments: 0.3 MB (<1%)
Archival Packages: 11.2 MB (8%)
Average PDF Size: 2.7 MB
Largest Paper: REF-015 (12.4 MB, book chapter)
Smallest Paper: REF-031 (0.4 MB, short paper)
Topic Coverage:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
agentic-workflows ████████████████ 24
llm-evaluation ████████████ 18
human-in-the-loop ██████████ 14
multi-agent-systems ████████ 12
cognitive-scaffolding ██████ 9
prompt-engineering ██████ 8
tool-use █████ 7
reproducibility █████ 6
fair-principles ████ 5
test-generation ████ 4
Research Gaps Identified:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠ Limited coverage of:
- Agent security (2 papers, recommend 5+)
- Cost optimization (1 paper, recommend 5+)
- Real-world case studies (3 papers, recommend 10+)
⚠ Date range gaps:
- 2019-2020: Only 4 papers (consider historical context)
⚠ Source diversity:
- Heavy arXiv reliance (32% preprints)
- Recommend more journal articles for HIGH GRADE sources
Health Score Breakdown:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Completeness: 18/20 (90%)
Integrity: 20/20 (100%)
Quality: 18/20 (90%)
Coverage: 16/20 (80%)
Policy Compliance: 20/20 (100%)
────────────────────────────────────────────
Overall Health Score: 92/100 (GOOD)
Recommendations:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
High Priority:
1. Complete quality assessments for REF-044, REF-045
2. Archive recently acquired papers (REF-041-045)
Medium Priority:
3. Add literature notes for 9 papers lacking synthesis
4. Enrich metadata (keywords for 9 papers, abstracts for 1)
5. Fill research gaps: agent security, cost optimization
Low Priority:
6. Add more pre-2020 papers for historical context
7. Increase journal article proportion for HIGH GRADE sources
Maintenance Schedule:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Weekly:
- Run /research-status --validate-all
- Archive new acquisitions
- Update literature notes
Monthly:
- Citation policy audit
- GRADE reassessment for preprints (check for publication)
- Fixity verification
- Generate synthesis reports
Quarterly:
- Topic coverage review
- Research gap analysis
- Corpus pruning (remove obsolete sources)
```
### Problems Only Mode
```
/research-status --problems-only
Research Corpus Issues
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
CRITICAL Issues (0):
None found
HIGH Priority Issues (2):
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠ Missing Quality Assessments:
- REF-044 (acquired 7 days ago)
Action: /research-quality REF-044
- REF-045 (acquired 5 days ago)
Action: /research-quality REF-045
MEDIUM Priority Issues (5):
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠ Missing Archival Packages:
- REF-041, REF-042, REF-043, REF-044, REF-045
Action: /research-archive REF-041 REF-042 REF-043 REF-044 REF-045
LOW Priority Issues (9):
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚠ Missing Literature Notes:
- REF-012, REF-015, REF-023, REF-028, REF-031, REF-038, REF-041, REF-044, REF-045
Action: /research-document [REF-XXX] --depth comprehensive
INFO Issues (3):
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
ℹ Missing Keywords:
- REF-012, REF-018, REF-023, REF-028, REF-031, REF-038, REF-041, REF-044, REF-045
Action: Update frontmatter manually or re-run metadata extraction
Summary:
Total Issues: 19
Critical: 0
High: 2
Medium: 5
Low: 9
Info: 3
Suggested Actions:
# Fix high priority issues
/research-quality REF-044 REF-045
# Fix medium priority issues
/research-archive REF-041 REF-042 REF-043 REF-044 REF-045
# Address low priority issues (optional)
/research-document REF-012 --depth comprehensive
```
## Health Score Calculation
```
Health Score = weighted_sum(
completeness_score * 0.25,
integrity_score * 0.25,
quality_score * 0.20,
coverage_score * 0.15,
compliance_score * 0.15
)
Completeness = % artifacts with all required elements
Integrity = % passing fixity/provenance checks
Quality = GRADE distribution (higher is better)
Coverage = Topic diversity and gap analysis
Compliance = Citation policy and standards adherence
Score Ranges:
90-100: EXCELLENT
80-89: GOOD
70-79: FAIR
60-69: NEEDS IMPROVEMENT
<60: CRITICAL
```
## Scheduled Reports
Generate scheduled reports:
```bash
# Daily summary
/research-status --export json > .aiwg/research/reports/daily-$(date +%Y%m%d).json
# Weekly detailed
/research-status --detailed --export markdown > .aiwg/research/reports/weekly-$(date +%Y%m%d).md
# Monthly with citation audit
/research-status --validate-all --check-citations --export yaml > .aiwg/research/reports/monthly-$(date +%Y%m%d).yaml
```
## References
- @$AIWG_ROOT/agentic/code/frameworks/research-complete/agents/workflow-agent.md - Status monitoring
- @$AIWG_ROOT/src/research/services/status-service.ts - Health check implementation
- @.aiwg/research/fixity-manifest.json - Integrity tracking
- @.aiwg/research/README.md - Corpus structure
- @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/rules/citation-policy.md - Policy complianceRelated Skills
customize-status
Show current AIWG customization status — mode, source path, what you've customized vs upstream
soul-status
Show SOUL.md enforcement state across all installed providers with quality check
rlm-status
Show status of RLM task tree execution
research-workflow
Execute multi-stage research workflows
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-provenance
Query provenance chains and artifact relationships
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