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-oauth-oidc-chaingit 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-oauth-oidc-chain)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-oauth-oidc-chain"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-oauth-oidc-chain/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-oauth-oidc-chain"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-oauth-oidc-chain.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 | $0.00119 | $0.00680 |
| Opus 5 | $0.00060 | $0.00340 |
| Sonnet 5 | $0.00024 | $0.00136 |
| Haiku 4.5 | $0.00012 | $0.00068 |
Grade A, and why
competition-oauth-oidc-chain 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 10d 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-oauth-oidc-chain — 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 OAuth OIDC Chain
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 hard part is proving how an OAuth or OIDC flow is shaped, exchanged, and ultimately accepted.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Map the auth chain in order: entry route, redirect, authorize request, callback, token exchange, refresh, and final accepting service.
- Record scopes, state, nonce, PKCE material, redirect URIs, and claim-bearing tokens before mutating anything.
- Separate token possession from actual identity acceptance.
- Keep browser-visible redirects and backend-visible token exchange in one compact chain.
- Reproduce the smallest redirect-to-acceptance flow that proves the decisive identity edge.
Workflow
1. Map The Redirect And Token Path
- Record issuer, client ID, redirect URI, authorize parameters, callback parameters, token endpoint, and refresh path.
- Note which values are user-controlled, derived, cached, or validated:
state,nonce, PKCE verifier, audience, scope, or prompt. - Keep browser redirects, server-side exchanges, and resulting session state tied together.
2. Prove Token-To-Identity Acceptance
- Show how code, ID token, access token, or refresh token turns into app session, claims mapping, tenant selection, or accepted privilege.
- Record token claims, expiration, audience, subject, scopes, and the exact accepting app or backend edge.
- Distinguish UI login success from backend authorization success.
3. Reduce To The Decisive OAuth Chain
- Compress the result to the smallest sequence: entry request -> redirect -> callback -> token or claim acceptance -> resulting capability.
- Keep one canonical good flow and one minimal mutated flow if a parameter change matters.
- If the task broadens into generic web routing or storage behavior outside the auth chain, switch back to the broader web-runtime 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.
- 10d ago First seen · 52 lines · 119 tokens per session scan A 47d4f2a26bee
competition-oauth-oidc-chain is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (2 stars, last pushed 26d ago), licensed MIT. It adds 119 tokens to every session and 680 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competition-oauth-oidc-chain, differing in 0 lines, and is treated as a copy.
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