Individual skill
competition-agent-cloud
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AI-agent, prompt-injection, MCP or toolchain, cloud, container, CI/CD, and supply-chain challenges. Use when the user asks to analyze prompt-to-tool flows, retrieval poisoning, mounted secrets, deployment drift, runtime-vs-manifest mismatches, registry provenance, or CI-produced artifacts under sandbox assumptions. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
CTF-Sandbox-Orchestrator/competition-agent-cloud/SKILL.md
Source commit cab634bd855fc287f6e420c1f36fd1a6b9245960
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 44,326
- Repository last updated
- Sep 22, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- devops Derived category
- operations Derived category
- devops-containers Derived category
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SKILL.mdcore · 4,009 bytesSKILL.mdcore · 4,009 bytesSKILL.mdcore · 4,009 bytesagents/openai.yamlasset · 379 bytesreferences/agent-cloud.mddoc · 1,085 bytes
Read excerpt
# Competition Agent Cloud
Use this skill only as a downstream specialization after `$ctf-sandbox-orchestrator` is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to `$ctf-sandbox-orchestrator` first.
Use this skill when the challenge path is driven by prompt-to-tool execution, retrieval and memory boundaries, deployment drift, or build and release provenance.
Reply in Simplified Chinese unless the user explicitly requests English.
## Quick Start
1. Decide whether the dominant path is agentic or infrastructure-driven.
2. Map one minimal control chain: untrusted input -> visible context -> tool or deployment side effect.
3. Distinguish checked-in intent from live runtime truth.
4. Keep prompts, tool args, manifests, mounts, and provenance steps in compact evidence blocks.