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 adriannoes/awesome-agentic-ai --skill redteam-mindsetgit clone --depth 1 https://github.com/adriannoes/awesome-agentic-aiWrote 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/adriannoes/awesome-agentic-ai/redteam-mindset)<a href="https://agentmods.dev/skills/adriannoes/awesome-agentic-ai/redteam-mindset"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/redteam-mindset/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/adriannoes/awesome-agentic-ai/redteam-mindset"><img src="https://agentmods.dev/badge/skills/adriannoes/awesome-agentic-ai/redteam-mindset.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 | $0.00094 | $0.05855 |
| Opus 5 | $0.00047 | $0.02927 |
| Sonnet 5 | $0.00019 | $0.01171 |
| Haiku 4.5 | $0.00009 | $0.00585 |
Grade A, and why
redteam-mindset 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 7d 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
86% identical to redteam-mindset — 39 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 — 388 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to use this skill
Trigger when:
- Engagement scope says "red team", "adversary emulation", "assume breach", "TIBER-style"
- You're tempted to retract a finding because reproducibility failed once
- You're tempted to call a defense "working as intended" instead of probing further
- You hit a blocker (captcha, rate limit, WAF, CA-block, lockout) and consider stopping
- You're about to spend time on IDOR/CSRF/XSS instead of access-yielding bugs
- You found a vuln on app A and there are sister apps B, C, D you haven't touched
DO NOT use for:
- Bug bounty programs (use bug-bounty skill — different scope rules)
- WAPT/PCI-style assessments (use OWASP-aligned skills)
- Pure compliance audits
The one-line summary
Red team scope = "gain access, prove impact". Bug bounty / WAPT scope = "find a bug, write a report".
These produce DIFFERENT decisions at every blocker. Internalize the difference before starting.
DO NOT STOP — primary directive (read this twice)
The 9 corrections below are nuance. THIS is the core. If you only retain one thing from this skill, retain this.
Authorization given at engagement start covers the entire engagement.
Do not insert mid-engagement permission gates. If the user chose a mode at the start ("full engagement", "Option D", "go deep", "test these assets") that authorization stands until the engagement window expires or the user explicitly revokes it. AskUserQuestion mid-loop after the user already chose a path is a stall, not a check.
Discipline rules are about correctness of FINDINGS, not throttling of EFFORT.
Read this twice. The bundle's discipline rules — OOB-Or-It-Didn't-Happen, Marker Discipline, Body-Diff, Pre-Severity Gate, Server-Policy-vs-State, Statistical Sampling — all answer one question: "is this signal actually a finding?". None of them answer the question "should I send the next probe?" The answer to that second question is always yes, unless scope is exhausted or the user said stop.
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.
- 7d ago First seen · 388 lines · 94 tokens per session scan A 2dc462992616
redteam-mindset is a skill published in the GitHub repository adriannoes/awesome-agentic-ai (57 stars, last pushed 12d ago), licensed MIT. It adds 94 tokens to every session and 5,855 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to redteam-mindset, differing in 39 lines, and is treated as a copy.
Other skills, from other repositories
importing-a-codebase
Use when the repo holds real source code but no specs: the existing-codebase branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for empty workspaces (starting-a-new-project) or feature work in a specced project (brainstorming).
starting-a-new-project
Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
brainstorming
Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.