Open research · 2026 edition

State of Agent Skills 2026.

A transparent look at what is actually inside an agent-skill registry: which records look like reusable skills, which are maintained, which declare a license, what can be installed, and how little real outcome evidence the ecosystem still has.
62
Indexed candidates
62
Analyzed sample
79%
Strict agent skills
0
Agent Proven

Executive finding

Popularity is not readiness.

GitHub adoption is useful, but it does not prove task fit, safe installation, or a successful agent run. This report keeps those signals separate.

  1. 0179% of the analyzed sample has strict Agent Skill evidence in its repository name, README, description, or topics.
  2. 026.5% describes an agent workflow or agent product without strict reusable-skill evidence.
  3. 0312.9% is better described as a domain workflow tool or ecosystem dependency than a strict agent skill.
  4. 041.6% is a list or collection rather than one installable skill.
  5. 0588.7% was pushed within 180 days of report generation.
  6. 0685.5% has a declared license that is not marked unknown.
  7. 0798.4% reaches the current 72-point high-trust threshold in this quality-ranked sample; Trust remains a metadata signal, not proof of task success.
  8. 080 analyzed skills have at least one reported agent outcome, covering 0 outcomes in total.

Readiness signals

What the analyzed sample can support.

Maintained within 180 days
5589%
Known license
5385%
Install path available
00%
500+ GitHub stars
5284%
72+ Trust Score
6198%
Safe-to-try audit
2540%

Domain coverage

Where the candidate supply is concentrated.

Track assignment uses category, task, use-case, and repository text signals. It is a discovery aid, not a claim that every record is production ready.

TrackCandidatesShareMaintainedKnown licenseHigh trust
Finance and quant workflows2540.3%192225
Design and creative production1625.8%151615
Coding and developer agents1117.7%11911
Research and knowledge work58.1%545
Football and World Cup analytics23.2%202
Marketing and growth automation23.2%222
General agent automation11.6%101

Evidence shortlist

Leading strict skill candidates.

Ordered by reported outcomes, Trust Score, skill-likeness, and GitHub adoption. This is a shortlist for evaluation, not an automatic-install endorsement.

Agent Proven ranking
SkillTrackStarsTrustAuditRiskOutcomes
Taste Skill: Anti-Slop Frontend
Leonxlnx/taste-skill
Design and creative production66K9191Safe to try0
Vercel React Best Practices
vercel-labs/agent-skills
Coding and developer agents29K9191Safe to try0
Frontend Design
anthropics/skills
Design and creative production163K8990Safe to try0
Anthropic Brand Guidelines
anthropics/skills
Design and creative production163K8990Safe to try0
Figma Implement Design
openai/skills
Design and creative production24K8889Safe to try0
Canvas Design
anthropics/skills
Design and creative production163K8889Safe to try0
Web Design Guidelines
vercel-labs/agent-skills
Design and creative production29K8889Safe to try0
Webapp Testing
anthropics/skills
Coding and developer agents163K8789Safe to try0
Deploy to Vercel
vercel-labs/agent-skills
Coding and developer agents29K8588Safe to try0
Playwright Browser Skill
openai/skills
Coding and developer agents24K8487Safe to try0
Equity Research Earnings Analysis
anthropics/financial-services
Finance and quant workflows34K8390Needs review0
Portfolio Monitoring
anthropics/financial-services
Finance and quant workflows34K8389Needs review0
Seedance 2.0 Prompt Writing
dexhunter/seedance2-skill
Design and creative production2.9K8386Safe to try0
3-Statement Financial Model
anthropics/financial-services
Finance and quant workflows34K8390Needs review0
Earnings Preview
himself65/finance-skills
Finance and quant workflows3.1K8189Needs review0
US Stock Analysis
tradermonty/claude-trading-skills
Finance and quant workflows2.6K8189Needs review0
Earnings Calendar
tradermonty/claude-trading-skills
Finance and quant workflows2.6K8189Needs review0
Company Valuation
himself65/finance-skills
Finance and quant workflows3.1K8189Needs review0
Market Environment Analysis
tradermonty/claude-trading-skills
Finance and quant workflows2.6K8189Needs review0
Aaron Marketing Skills
aaron-he-zhu/aaron-marketing-skills
Marketing and growth automation2.3K8088Safe to try0
Market News Analyst
tradermonty/claude-trading-skills
Finance and quant workflows2.6K7988Needs review0
David Ondrej Skills
davidondrej/skills
Coding and developer agents9687988Safe to try0
Vox Director
Alisa0808/vox-director
Design and creative production3267987Safe to try0
Seedance 2.0 Skill
Emily2040/seedance-2.0
Design and creative production8.0K7987Safe to try0
Last30days Skill
mvanhorn/last30days-skill
Research and knowledge work43K7986Safe to try0

Methodology

Readable before repeatable.

Published Jul 10, 2026. Data refreshed Oct 22, 2026.

Population and sample

All public records with ai_review_approved=true in the OpenAgentSkill registry. MCP-only records are excluded by the registry read layer.

The highest-ranked 62 approved candidates by the current quality ordering. The sample is a product audit, not a random statistical sample.

Inclusion and measurement

  • •Public GitHub repository or repository URL is available
  • •Registry AI review is approved
  • •MCP-only server records are excluded
  • •Skill-likeness is measured separately from repository popularity
  • •Trust and audit scores use public repository metadata and declared install information

Limitations

  • •GitHub stars measure repository adoption, not agent task success
  • •Candidate listings are not equivalent to verified maintainer claims
  • •A public metadata audit is not a substitute for source review or sandbox execution
  • •Agent Proven evidence remains sparse until agents report real outcomes
  • •Repository metadata can change after this report is generated

For a fixed dataset and reproducible comparison of declared license and install-path fields, read the October 18, 2026 readiness snapshot. The snapshot preserves the source response and documents its sample limitations.

Cite this report

OpenAgentSkill. “State of Agent Skills 2026.” Published July 10, 2026. Dataset and methodology available at https://www.openagentskill.com/reports/state-of-agent-skills-2026.