market-research-reports
No security findings. Scanned 1 time, most recently 2026-10-21.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Builds evidence-traceable market research reports and assumption-driven market sizing or forecast scenarios. Use for market definition, industry and customer evidence, competitive landscapes, TAM/SAM/SOM reconciliation, forecast sensitivity, and auditable report scaffolds.
- Package
- 26 files, 189 KB
- SKILL.md
- 1830 words, 12+ sections
- Code
- Python (8)
- License
- MIT
- Compatibility
- Python 3.11+ standard library for optional offline CLIs. The optional LaTeX template uses XeLaTeX or LuaLaTeX. Online research requires user-approved network access and source-specific terms; bundled scripts make no network, LLM, or image calls.
SKILL.md covers: Market Research Reports · Purpose · Operating principles · Workflow · 1. Establish the research contract · 2. Build the evidence plan · 3. Create the source ledger · 4. Maintain a claims ledger · 5. Size the market as scenarios · 6. Forecast with explicit uncertainty · 7. Analyze customers and primary research · 8. Analyze competitors and concentration
Findings
No findings. SAFE
What is in the package
26 files, 189 KB. Show the list.
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 15 KB |
assets/FORMATTING_GUIDE.md | doc | 5.8 KB |
assets/claims_ledger_template.csv | data | 957 B |
assets/competitor_feature_matrix_template.csv | data | 683 B |
assets/consistency_check_template.csv | data | 432 B |
assets/forecast_sensitivity_template.json | config | 1.8 KB |
assets/market_report_template.tex | data | 9.8 KB |
assets/market_research.sty | other | 6.3 KB |
assets/market_sizing_scenarios_template.json | config | 3.1 KB |
assets/report_manifest_template.json | config | 882 B |
assets/source_ledger_template.csv | data | 1.3 KB |
references/data_analysis_patterns.md | doc | 9.8 KB |
references/evidence_model.md | doc | 6.0 KB |
references/methods_and_ethics.md | doc | 7.9 KB |
references/official_data_sources.md | doc | 11 KB |
references/report_structure_guide.md | doc | 8.4 KB |
references/sources.md | doc | 10 KB |
references/visual_generation_guide.md | doc | 5.1 KB |
scripts/_common.py | script | 11 KB |
scripts/audit_claim_citations.py | script | 11 KB |
scripts/calculate_market_sizing.py | script | 13 KB |
scripts/check_unit_consistency.py | script | 7.0 KB |
scripts/forecast_sensitivity.py | script | 11 KB |
scripts/generate_report_scaffold.py | script | 15 KB |
scripts/validate_competitor_matrix.py | script | 7.6 KB |
scripts/validate_evidence_ledger.py | script | 9.0 KB |
External hosts referenced
www.census.gov aapor.org ec.europa.eu fred.stlouisfed.org www.oecd.org www.sec.gov www.whitehouse.gov eur-lex.europa.eu statspolicy.gov www.justice.gov apps.bea.gov arxiv.org ctan.org data.imf.org datacatalog.worldbank.org datahelpdesk.worldbank.org developer.ons.gov.uk ico.org.uk www.bea.gov www.bls.gov www.gov.uk www.statcan.gc.ca docs.python.org doi.org dsbb.imf.org export.arxiv.org force11.org
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Package contents recorded 2026-10-22 at commit 593377bb0487. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Bytecode analyzer.
- Pipeline analyzer.
- Correlation analyzer.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/K-Dense-AI/scientific-agent-skills
- Raw scan result: skills-market-research-reports-scan.json
- Badge for your README:
- Request a re-scan