audit-context-building
Uses First Principles and 5 Whys to perform deep-dive code analysis before vulnerability assessment.
Install
mkdir -p .claude/skills/audit-context-building && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/5917" && unzip -o skill.zip -d .claude/skills/audit-context-building && rm skill.zipInstalls to .claude/skills/audit-context-building
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.
Enables ultra-granular, line-by-line code analysis to build deep architectural context before vulnerability or bug finding.Key capabilities
- →Perform line-by-line code analysis
- →Apply First Principles and 5 Whys to code blocks
- →Construct a persistent global mental model
- →Trace data flow across internal and external calls
- →Identify invariants and assumptions
How it works
It executes a systematic, block-by-block analysis to build a stable mental model of system logic and assumptions before any security auditing occurs.
Inputs & outputs
When to use audit-context-building
- →Performing threat modeling
- →Deep architectural review
- →Pre-audit code understanding
About this skill
Audit Context Building
Build understanding, not verdicts. This runs before anyone hunts for bugs, and feeds that work.
When to Use
At the start of an audit, a threat model, or an architecture review, when the code is unfamiliar. Also when an earlier pass produced findings nobody could judge, because no one had mapped out how the system fits together.
When NOT to Use
Do not name vulnerabilities, suggest fixes, write proofs-of-concept, or rate severity. Those belong to the hunting phase, which runs next and with the whole picture in hand. When the code counts on something and nothing checks it, record that plainly and move on — whether it matters is decided later.
Not worth the tokens on code you already understand.
Do not analyze in this context
The analysis is long, and this context needs to survive to use it. Dispatch it:
- A codebase, or more than one function — run
/audit-context-building:audit-context <path>. It orients, analyzes each function in its own subagent, and writesaudit-context/DOSSIER.mdplus one file per function underaudit-context/functions/. Only compact records return here. - A single function — dispatch the
audit-context-building:function-analyzeragent at it. It writes its prose to disk and returns a record.
Then work from what comes back: the index, the unenforced assumptions, the open questions. Read a function's file when you need its detail.
The workflow is what enforces this, not this text: a subagent bound to a return schema cannot return prose. Treat this section as routing, and route.
What comes back, and how to read it
Each record lists what must always be true (with the line that shows it), what the function takes on faith (with whatever establishes it), which functions it calls and what it needs from each, and anything still unclear. The dossier adds the rules that span several functions, who can reach what, and where the complicated parts cluster.
Two things matter more than the rest:
- Assumptions marked
nothing found. The code counts on something being true and nothing anywhere makes it true. This is the most useful thing to hand the hunting phase. - The open questions. An honest list of what is still unclear beats a confident answer that turns out to be wrong. Carry them forward instead of closing them out.
Where two records disagree, both are quoted rather than quietly reconciled. That is a fact about the code, not a flaw in the analysis.
The format
ANALYSIS_FORMAT.md defines it, and FUNCTION_MICRO_ANALYSIS_EXAMPLE.md works through examples in C and Solidity. Read them when extending this plugin or deciding whether a record can be trusted.
The format is the same whatever the target. What changes is what fills each slot, and what counts as a call you cannot see inside. DOMAIN_NOTES.md maps that across smart contracts, C and C++, decompiled firmware, and web services — read it when the target is not plain source code.
The rule that matters most: follow the calls. Whether a function is correct usually depends on something
another function does, and you cannot see that from the caller alone. A limit looks enforced because the
value came back from a function whose name suggests it was checked. So read the function being called, follow
every path through it rather than only the one that succeeds, and say what makes each assumption true. When
nothing does, use those words: nothing found. Every claim cites a line, or becomes an open question.
When not to use it
- →Vulnerability finding
- →Fix recommendations
- →Exploit reasoning
Limitations
- →Not for vulnerability identification
- →Requires manual inspection of external calls without code
- →Strict adherence to output format is mandatory
How it compares
It mandates a bottom-up, ultra-granular analysis approach instead of high-level architectural guessing.
Compared to similar skills
audit-context-building side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| audit-context-building (this skill) | 1 | 2mo | No flags | Advanced |
| software-security | 21 | 6mo | No flags | Intermediate |
| fix-dependabot-alerts | 18 | 6mo | Review | Intermediate |
| backend-security-coder | 24 | 4mo | No flags | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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