Dependency Updater (softaworks) vs Semgrep Rule Creator (trailofbits)
Dependency Updater (softaworks) and Semgrep Rule Creator (trailofbits) are both Security skills, so an agent choosing between them is matching on descriptions that overlap. Here is where they actually diverge.
Dependency Updater
softaworks
Works over a project's dependency manifest — detecting the language, applying the safe minor and patch bumps on its own, pausing on major versions, and running that ecosystem's vulnerability audit (npm audit, pip-audit, govulncheck, cargo audit and the like) to flag known-vulnerable packages. It secures the supply chain around your code, not the code itself: it does not scan your own source for bugs, write detection rules, or reason about a design's threats.
3 scenarios in the bank answer to it
Semgrep Rule Creator
trailofbits
Authors a custom Semgrep static-analysis rule for one specific bug or vulnerability pattern — building the match (or a taint-mode source-to-sink data flow), then the paired vulnerable-and-safe test cases that keep false positives in check. Its output is a reusable detection rule, not a finished audit: it does not run existing Semgrep rulesets over your repo, triage the findings a scan produces, or review a diff by hand.
1 scenario in the bank answer to it
What is the difference between Dependency Updater (softaworks) and Semgrep Rule Creator (trailofbits)?
- Dependency Updater (softaworks)
- Works over a project's dependency manifest — detecting the language, applying the safe minor and patch bumps on its own, pausing on major versions, and running that ecosystem's vulnerability audit (npm audit, pip-audit, govulncheck, cargo audit and the like) to flag known-vulnerable packages. It secures the supply chain around your code, not the code itself: it does not scan your own source for bugs, write detection rules, or reason about a design's threats.
- Semgrep Rule Creator (trailofbits)
- Authors a custom Semgrep static-analysis rule for one specific bug or vulnerability pattern — building the match (or a taint-mode source-to-sink data flow), then the paired vulnerable-and-safe test cases that keep false positives in check. Its output is a reusable detection rule, not a finished audit: it does not run existing Semgrep rulesets over your repo, triage the findings a scan produces, or review a diff by hand.
Should I use Dependency Updater or Semgrep Rule Creator?
The clearest answer is a situation each one is unambiguously right for. Both of these are drawn from the game's question bank.
Reach for Dependency Updater when
A beloved open-source gadget is stuck on an ancient Rails release. The maintainer wants to float through incremental updates and sniff for tainted third-party libraries before the morning build kicks off.
This skill specializes in lazily massaging a repository's dependency graph—automatically elevating low-risk point improvements, parking large jumps, then querying the ecosystem's own defect registry for poisoned artifacts. It wins because the scenario is purely about keeping third-party libraries healthy before a build, not about hunting source-code bugs, writing detection rules, or surfacing failures correctly.
Reach for Semgrep Rule Creator when
At a security audit you discover your app mishandles a proprietary protocol in a way command-line scanners default ignore. You need to codify a narrowly scoped gatekeeper with paired illustrations to avoid noisy CI runs.
The skill is designed for narrowing the focus to exactly one novel weakness in code, teaching how to build a pair of contrasting code snippets and package them into a portable, reusable gatekeeper that plugs into CI. That fits here because the bug is proprietary and off-the-shelf checkers are blind to it, so you need a self-contained, narrowly scoped artifact with paired positive and negative illustrations rather than a supply-chain sweep, a generic error-message rewrite, or an identity breach lookup.
What they have in common
Both are filed under Security, the axis along which they collide. That shared ground is what makes an agent pick between them on description alone — and what makes it pick wrong.
Nearby comparisons
Reading the difference is not the same as spotting it at speed. That is the game.
Today's session