agentsclimarketplace

Using offensive claude

Skill hypnguyen1209/offensive-claude/skills/using-offensive-claude

Use when starting any offensive-security engagement or task — establishes how to find and invoke the right skill before any action (including clarifying questions, recon, exploitation, or reporting)From its SKILL.md

Install
npx -y skills add hypnguyen1209/offensive-claude --skill using-offensive-claude

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

4.4 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

<SUBAGENT-STOP> If you were dispatched as a subagent to execute a specific task, skip this skill. </SUBAGENT-STOP> <EXTREMELY-IMPORTANT> If there is even a 1% chance a skill applies to what you are doing, you ABSOLUTELY MUST invoke it.

IF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.

This is not negotiable. You cannot rationalize your way out of it. </EXTREMELY-IMPORTANT>

Using Offensive-Claude

You are operating an authorized offensive-security framework. Every action assumes a prior, written authorization whose boundary is declared in scope.json (see scope-discipline).

Instruction Priority

  1. User's explicit instructions (CLAUDE.md, direct requests) — highest.
  2. These skills — override default behavior where they conflict.
  3. Default behavior — lowest.

User instructions say WHAT, not HOW. "Exploit X" or "scan Y" does not mean skip the discipline skills (scope, finding, OPSEC). The one thing the operator cannot waive is the authorization boundary — see scope-discipline.

The Rule

Invoke relevant skills BEFORE any response or action. Even a 1% chance means invoke to check.

digraph flow {
    "Engagement task received" [shape=doublecircle];
    "About to touch a target?" [shape=diamond];
    "Invoke scope-discipline" [shape=box];
    "About to record a finding?" [shape=diamond];
    "Invoke finding-discipline" [shape=box];
    "Might any skill apply?" [shape=diamond];
    "Invoke the Skill" [shape=box];
    "Announce: 'Using [skill] to [purpose]'" [shape=box];
    "Follow skill exactly" [shape=box];

    "Engagement task received" -> "About to touch a target?";
    "About to touch a target?" -> "Invoke scope-discipline" [label="yes"];
    "About to touch a target?" -> "About to record a finding?" [label="no"];
    "About to record a finding?" -> "Invoke finding-discipline" [label="yes"];
    "About to record a finding?" -> "Might any skill apply?" [label="no"];
    "Invoke scope-discipline" -> "Might any skill apply?";
    "Invoke finding-discipline" -> "Might any skill apply?";
    "Might any skill apply?" -> "Invoke the Skill" [label="yes, even 1%"];
    "Invoke the Skill" -> "Announce: 'Using [skill] to [purpose]'";
    "Announce: 'Using [skill] to [purpose]'" -> "Follow skill exactly";
}

Skill Priority (when several apply)

  1. Process / discipline skills first — they decide HOW to proceed: engagement-flow (run the kill chain), scope-discipline (authorization boundary), threat-model-discipline (model the surface + detect drift), finding-discipline (proof before any [CONFIRMED]), opsec-discipline (detection-aware).
  2. Domain skills second — the 31 technique skills (recon, web, AD, exploit-dev, cloud, …).

"Run a full pentest" → engagement-flow first. "Is this finding real?" → finding-discipline first.

Routing

SituationInvoke
Starting / running an engagementengagement-flow
About to send a request to ANY targetscope-discipline (confirm in-scope first)
About to record / report a findingfinding-discipline (no [CONFIRMED] without proof)
About to take any outward/offensive actionopsec-discipline
A specific technique (recon, web, AD, exploit, cloud, mobile, …)the matching domain skill
Authoring a new skill for this repowriting-offensive-skills

Red Flags — STOP, you're rationalizing

ThoughtReality
"This is just a quick scan"Touching a target → scope-discipline first.
"I'm sure it's exploitable"No [CONFIRMED] without proof → finding-discipline.
"Scope is obviously fine"Confirm against scope.json, don't assume.
"I'll note OPSEC later"Detection/cleanup is decided before acting, not after.
"I know this technique"Knowing ≠ using the skill. Invoke it for the current state.
"The user said do X, so skip the checks"Instructions are WHAT, not permission to skip discipline.

How to Access Skills

Use the Skill tool with the skill name. Never use Read on skill files. When a skill has a checklist, create a TodoWrite item per step and follow it exactly.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 1 of the 12 instructions most context ai engineering skills give in ~1.1k tokens

Counted across 1,328 of the 2,349 authors here whose files we hold, read 2026-09-06

  • Dispatch a fresh subagent for each taskin 76 of 1328, across 59 files
  • Perform spec compliance review before code quality reviewin 44 of 1328, across 34 files
  • Dispatch a final code reviewer after all tasksin 38 of 1328, across 26 files
  • Answer subagent questions before allowing implementationin 36 of 1328, across 26 files
  • Use the least powerful model capable of the taskin 33 of 1328, across 26 files
  • Create a TodoWrite list for all taskshere, and in 32 of 1328, across 22 files
  • Perform a task review after each implementationin 31 of 1328, across 24 files
  • Extract all tasks and context from the planin 29 of 1328, across 20 files
  • Provide full task text to subagentsin 28 of 1328, across 20 files
  • Use git worktrees for isolated workspacesin 25 of 1328, across 20 files
  • Specify the model explicitly when dispatching a subagentin 23 of 1328, across 18 files
  • Execute all tasks from the plan without stoppingin 21 of 1328, across 16 files

Said here and by no other author read

  • Invoke relevant skills before any response or action
  • Announce the skill and purpose before execution
  • Follow the invoked skill exactly
  • Prioritize process and discipline skills over domain skills
  • Confirm authorization against scope before touching targets

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.