Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory

by frenzymath · Codex Skill · ★ 356

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

Security audit verdict: SAFE · quality 61/100

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.

agentsai4mathautomated-reasoningclaude-codecodexllmmathematicsmulti-agent

Quick Facts

Stars356
Forks54
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score61/100
Open Issues1
Last Updated2026-08-27
Created2026-07-07
Platformsclaude-code, codex, python
Est. Tokens~15k

About Danus

Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory Danus orchestrates mathematical reasoning agents with fact-graph memory. A main agent (Claude Code) steers a swarm of autonomous codex workers that prove; a cold-start verifier is the sole authority on correctness: a result becomes real only once it passes.

Compatible Skills

These tools work well together with Danus for enhanced workflows:

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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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