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 skills add Asaiuta/reverse-workbench-skill --skill competition-cloud-metadata-pathgit clone --depth 1 https://github.com/Asaiuta/reverse-workbench-skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-cloud-metadata-path)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-cloud-metadata-path"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-cloud-metadata-path/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-cloud-metadata-path"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-cloud-metadata-path.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00118 | $0.00675 |
| Opus 5.5 | $0.00047 | $0.00270 |
| Sonnet 5.5 | $0.00024 | $0.00135 |
| Haiku 4.5 | $0.00012 | $0.00068 |
Grade A, and why
competition-cloud-metadata-path 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 1mo 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-cloud-metadata-path — 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition Cloud Metadata Path
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 decisive edge is not just reaching metadata, but proving how metadata-derived identity becomes accepted privilege.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Identify which metadata surface is active: instance metadata, workload identity, node identity, task role, or platform-specific token endpoint.
- Record the exact reachability path: local process, pod, container, proxy, SSRF surface, or host route.
- Separate metadata reachability from credential issuance and from downstream privilege acceptance.
- Keep token format, role identity, scope, and accepting API in compact evidence blocks.
- Reproduce the smallest metadata-to-accepted-privilege path that proves the challenge edge.
Workflow
1. Map Metadata Reachability
- Record the metadata endpoint, required headers, hop limits, session tokens, workload selectors, or path prefixes.
- Note whether access comes from direct local calls, pod networking, SSRF, sidecar, or host-level routing.
- Keep the reaching surface and the metadata endpoint in one chain.
2. Prove Credential Or Identity Issuance
- Show how the metadata response becomes a token, temporary credential, signed identity doc, or platform-specific workload identity.
- Record expiration, role name, subject, audience, issuer, or cloud account mapping that matters downstream.
- Distinguish raw metadata from usable credential material.
3. Reduce To The Decisive Trust Path
- Compress the result to the smallest sequence: reaching surface -> metadata call -> credential issued -> accepted cloud or cluster action.
- State clearly whether the weakness lives in reachability, metadata config, role trust, downstream policy, or workload binding.
- If the challenge narrows to RBAC or cluster mutation after credential issuance, switch back to the tighter control-plane skill.
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.
- 1mo ago First seen · 52 lines · 118 tokens per session scan A 5f15e808652c
competition-cloud-metadata-path is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (4 stars, last pushed 2mo ago), licensed MIT. It adds 118 tokens to every session and 675 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to competition-cloud-metadata-path, differing in 0 lines, and is treated as a copy.
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