research-innovation-explorer: The automated approach leverages the cross-combination of high-quality papers from top conferences to uncover

by foryourhealth111-pixel · Codex Skill · ★ 86

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

academicagent-skillsai-scienceauto-researchautomationclaude-codecodexopenclaw-skillsresearchscience

Quick Facts

Stars86
Forks7
LanguagePython
CategoryCodex Skill
LicenseMIT
Quality Score68/100
Last Updated2026-08-14
Created2026-04-20
Platformsclaude-code, codex, python
Est. Tokens~16k

About research-innovation-explorer

Research Innovation Explorer A host-neutral, search-first skill for literature-grounded idea discovery, theory framing, and polished Markdown reporting. 中文文档 Why This Exists Most research-idea workflows fail in one of three ways: they rely on vague intuition instead of systematic search they generate combinations but cannot explain why the combination matters they stop at analysi

Compatible Skills

These tools work well together with research-innovation-explorer for enhanced workflows:

  • rigorous — semantic(0.30)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • Deep-Research-skills — semantic(0.25)+complementary+same_lang+similar_pop+shared_platform (59%)
  • stata-mcp — semantic(0.24)+complementary+same_lang+similar_pop+shared_platform (58%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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