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BF web3-audit

Smart contract security audit — 10 DeFi bug classes (accounting desync, access control, incomplete path, off-by-one, oracle, ERC4626, reentrancy, flash loan, signature replay, proxy), pre-dive kill signals (TVL < $500K etc), Foundry PoC template, grep patterns for each class, and real Immunefi paid examples. Use for any Solidity/Rust contract audit or when deciding whether a DeFi target is worth hunting.

elementalsouls/Claude-BugHunter Agent Skills author: elementalsouls 1 file body ≈ 5 847 tokens Open the sourcegithub.com↗ analyzed 2 h ago

Smart contract security audit — 10 DeFi bug classes (accounting desync, access control, incomplete path, off-by-one, oracle, ERC4626, reentrancy, flash loan…

As a process F 44/100 · Will not run — References files that are not bundled: 2

AnalyzerSoftware developmentFinanceData and analyticstype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
99
Quality 40%
67
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: 2
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
  2. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 1

✓ No critical or high findings

Medium and low: 1
  • low Risky intent intent-offensive-security SKILL.md:561
    Offensive-security / dual-use content (legitimate for authorised testing; review intended use)
    - **`bb-methodology`** — When deciding whether to dive at all. Workflow primitive: PART 0 of `bb-methodology` confirms engagement (web3 bug bounty / private audit / smart-contract review); this skill'

Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5847 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: 2
  • note frontmatter-key unknown frontmatter key "sources"

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: 2
  • 0Tools and files. 1 referenced file(s) missing: 2
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 4 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 70Execution cost. Instruction body is 5847 tokens
  • 100Steps. 31 steps
  • 100Failures and branches. 1 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • low 15 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 407: enough signal without eating the budget
  • +4Structure: 61 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (39 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.