elephant-goldfish-model: Open-source plugin for designing and reviewing software with agents

by google · Claude Skill · ★ 13.2k

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

Security audit verdict: SAFE · quality 63/100

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. Full audit →

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.

agent-skillsai-agentsantigravityclaude-codeclaude-code-pluginclaude-skillscodexcodex-plugincoding-agentscontext-engineering

Quick Facts

Stars13,187
Forks971
LanguagePython
CategoryClaude Skill
LicenseApache-2.0
Quality Score63/100
Open Issues74
Last Updated2026-11-07
Created2026-09-13
Platformsclaude-code, codex, gemini, python
Est. Tokens~14k

About elephant-goldfish-model

Elephant-Goldfish Model (EGM) Elephant-Goldfish Model is an open-source framework and methodology for Spec-Driven Development (SDD) with autonomous AI coding agents. It anchors development in context-rich system descriptions and adversarial multi-agent reviews, making complex codebases easier for both humans and AI to navigate, verify, and evolve.

Compatible Skills

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  • autospec — semantic(0.56)+complementary+similar_pop (54%)
  • Conductor-for-all — semantic(0.53)+complementary+similar_pop (53%)

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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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