Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/2233admin/reverse-skill-evolver/competition-agent-cloudnpx skills add 2233admin/reverse-skill-evolver --skill competition-agent-cloudgit clone --depth 1 https://github.com/2233admin/reverse-skill-evolverWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00107 | $0.00785 |
| Opus 5 | $0.00053 | $0.00392 |
| Sonnet 5 | $0.00021 | $0.00157 |
| Haiku 4.5 | $0.00011 | $0.00078 |
Grade A, and why
competition-agent-cloud scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to competition-agent-cloud — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
- Decide whether the dominant path is agentic or infrastructure-driven.
- Map one minimal control chain: untrusted input -> visible context -> tool or deployment side effect.
- Distinguish checked-in intent from live runtime truth.
- Keep prompts, tool args, manifests, mounts, and provenance steps in compact evidence blocks.
- Reproduce the exploit or misconfiguration with minimal context and minimal instrumentation.
Workflow
1. Agent And Prompt Injection
- Treat prompts, tool schemas, retrieved chunks, planner notes, memory files, and handoffs as challenge artifacts.
- Prove one minimal chain from untrusted content to model-visible instruction to tool side effect.
- Distinguish claimed capability from runtime-exposed capability.
2. Cloud, Containers, And CI/CD
- Split build-time, deploy-time, and runtime.
- Reconcile compose or kube manifests with live mounts, env, logs, and traffic.
- Trace provenance from source to dependency resolution to build to publish to runtime consumer.
Read This Reference
- Load
references/agent-cloud.mdfor the control-stack checklist, deployment-truth checklist, and evidence packaging. - If the task is specifically about prompt-boundary abuse or retrieved-content-to-tool drift, prefer
$competition-prompt-injection. - If the task is specifically about CI, dependency provenance, registry drift, or shipped artifacts, prefer
$competition-supply-chain. - If the task is specifically about queue payloads, async worker drift, retries, or worker-only runtime state, prefer
$competition-queue-worker-drift. - If the task is specifically about SSRF to internal control surfaces, metadata endpoints, or metadata-derived token pivots, prefer
$competition-ssrf-metadata-pivot. - If the task is specifically about proxy-upstream parse differentials, ambiguous headers, path normalization drift, or request smuggling behavior, prefer
$competition-request-normalization-smuggling. - If the task is specifically about metadata-service access, instance or workload identity, link-local token paths, or metadata-derived privilege, prefer
$competition-cloud-metadata-path. - If the task is specifically about kube API permissions, service-account trust, admission behavior, controller drift, or cluster secret exposure, prefer
$competition-k8s-control-plane. - If the task is specifically about live mounts, sidecars, init containers, or runtime-only secret exposure, prefer
$competition-container-runtime. - If the task is specifically about container-to-host boundary crossing, kernel-surface prerequisites, or escape primitive verification, prefer
$competition-kernel-container-escape.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 54 lines · 107 tokens per session scan A 9e56a603f14f
competition-agent-cloud is a skill published in the GitHub repository 2233admin/reverse-skill-evolver (13 stars, last pushed 22d ago), licensed MIT. It adds 107 tokens to every session and 785 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competition-agent-cloud, differing in 0 lines, and is treated as a copy.
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