Provides a research framework to translate high-level hunt topics into evidence-based security contexts.
Install
mkdir -p .claude/skills/hunt-research-system-and-tradecraft && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5882" && unzip -o skill.zip -d .claude/skills/hunt-research-system-and-tradecraft && rm skill.zipInstalls to .claude/skills/hunt-research-system-and-tradecraft
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Research system internals and adversary tradecraft to ground a threat hunt in real system behavior and realistic abuse patterns. Use this skill at the start of hunt planning, when you are given a high-level hunt topic but lack a clear understanding of how the system normally operates or how adversaries are known to abuse it. This skill informs early hunt direction by producing candidate abuse patterns, key assumptions, and cited sources, and should be used before defining a concrete hunt hypothesis or selecting data sources.Key capabilities
- →Defines specific system and platform scope
- →Identifies candidate adversary abuse patterns
- →Documents key assumptions for hunting
- →Normalizes ambiguous user input for security investigation
- →Establishes baseline behavior for system internals
How it works
It follows a strict step-by-step framework to decompose a vague threat topic into known system behaviors and documented abuse vectors.
Inputs & outputs
When to use hunt-research-system-and-tradecraft
- →Investigate adversary abuse patterns
- →Research system internals for threat analysis
- →Ground hunt planning in realistic behavior
- →Develop threat hunt context
About this skill
Research System Internals and Adversary Tradecraft
Provide structured research context at the start of a threat hunt by incrementally applying only the references explicitly called for in each workflow step. This skill establishes a grounded understanding of system capabilities and adversary behaviors so downstream hunt planning reflects how the environment actually works and how it is realistically abused.
Workflow
- You MUST complete each step in order and MUST NOT proceed until the current step is complete.
- You MUST NOT read reference documents or perform web searches unless the current step explicitly instructs you to do so.
- Do NOT output raw notes, coverage checks, intermediate reasoning, or step summaries.
- Do NOT restate findings from previous steps outside the final report structure.
Step 1: Normalize the input
Translate the user's high-level topic into a precise research scope before any investigation begins. This step exists to remove ambiguity and establish a shared frame for system and adversary analysis.
This step is complete only when the scope is explicit and unambiguous.
- Record the topic exactly as provided (e.g., "WMI abuse", "Kerberos abuse").
- Identify the concrete platform, system, or feature in scope.
- Resolve ambiguity by stating explicit assumptions when needed.
- Set the research intent to cover both normal system behavior and adversary abuse unless the user explicitly restricts it.
- If critical scope details are missing or ambiguous, request clarification from the user.
- If sufficient information is available, proceed without further confirmation.
Do NOT perform web searches or read reference documents during this step.
Step 2: Research system internals
Build a grounded understanding of how the system functions under normal conditions.
- Start with searching the web using
Tavily:tavily-search, and do not exceed 5 total web search queries in this step. - Stop searching once core system concepts, capabilities, and observability are sufficiently understood.
- Apply guidance from
references/tavily-search-guide.md. - Collect raw research notes focused on system behavior and capabilities.
During this step only:
- Evaluate coverage using
references/system-internals-research-guide.mdwithin this step ONLY. - If gaps are identified, perform targeted follow-up research (web or internal knowledge) and update the notes.
Do NOT read adversary tradecraft reference documents in this step. Do not synthesize or summarize findings.
Step 3: Research adversary tradecraft
Analyze how adversaries leverage or manipulate the system capabilities identified above.
- Start with searching the web using
Tavily:tavily-search, and do not exceed 5 total web search queries in this step. - Stop searching once dominant abuse behaviors and execution patterns are clearly understood.
- Apply guidance from
references/tavily-search-guide.md. - Collect raw research notes focused on behavior and outcomes, not tools.
During this step only:
- Evaluate coverage using
references/adversary-tradecraft-research-guide.mdwithin this step ONLY. - If gaps are identified, perform targeted follow-up research (web or internal knowledge) and update the notes.
Do Not read system internals reference documents in this step. Do Not synthesize or summarize findings.
Step 4: Identify candidate abuse patterns
Using the completed adversary tradecraft research, extract concrete abuse patterns that will guide hypothesis-driven hunting.
- Identify the top 3–5 distinct patterns (or fewer if one clearly dominates).
- For each pattern, record:
- Adversary behavior
- System capability or assumption being abused
- High-level observables or effects
- Common variations that preserve the same outcome
Porivide the list of patterns if they exist. They must be tool-agnostic and suitable for use in the next hunt-planning step.
Step 5: Write the research summary
Produce the final structured research artifact using the following documents within this step ONLY.
- Structure the output using
references/research-summary-template.md. - Format and cite sources using
references/research-citations-guide.md.
This step is synthesis only. Do not introduce new research, assumptions, or evidence at this stage.
When not to use it
- →When the investigation path is already defined
- →Security tasks not involving adversarial threats
Limitations
- →Restricts new web searches to prevent distraction
- →Only covers research, does not execute the hunt
How it compares
It forces a disciplined, evidence-based approach to scoping before any hypotheses are formed, unlike quick ad-hoc searching.
Compared to similar skills
hunt-research-system-and-tradecraft side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| hunt-research-system-and-tradecraft (this skill) | 1 | 7mo | No flags | Intermediate |
| red-team-tools-and-methodology | 7 | 6mo | Review | Advanced |
| hunt-focus-definition | 1 | 7mo | No flags | Intermediate |
| security-research | 0 | 4mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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