awesome-goal-prompts: Source-backed /goal contracts for Claude Code, Codex and Cursor, with a searchable catalog and separate

by majiayu000 · Claude Skill · ★ 51

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

Security audit verdict: SAFE · quality 58/100

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.

agent-skillsagent-workflowsagentic-aiai-agentsai-codinganthropic-claudeawesomeawesome-listclaude-codecodex

Quick Facts

Stars51
Forks6
LanguagePython
CategoryClaude Skill
LicenseCC0-1.0
Quality Score58/100
Last Updated2026-10-02
Created2026-05-13
Platformsclaude-code, codex, python
Est. Tokens~23k

About awesome-goal-prompts

Awesome Goal Prompts — Coding Agent Rescue Contracts When Claude Code, Codex, Cursor, or another coding agent starts making broad edits, paste a contract that says exactly what to inspect, what not to touch, how to verify, and when to stop. This repo keeps 300+ runnable contracts for engineering work.

Compatible Skills

These tools work well together with awesome-goal-prompts for enhanced workflows:

  • claude-prompts — semantic(0.24)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • prompt-architect — semantic(0.32)+complementary+rare_topics+same_lang+similar_pop+shared_platform (61%)
  • awesome-ai-plugins — semantic(0.27)+complementary+same_lang+similar_pop+shared_platform (59%)

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  • turbo-flow by marcuspat · ⭐ 184

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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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