Projects
inconnu
A Python data privacy library for redacting and pseudonymizing sensitive text with NLP-based entity detection.
harness
Opinionated project templates with built-in guardrails so AI coding agents produce reliable, maintainable code from the start.
How harness works
The problem: checks that drift
An agent can finish an edit while formatting, types, and tests disagree about whether the work is ready. Repeating the instructions in a prompt leaves the checks dependent on whoever remembers to run them.
The work: a shared command contract
Harness puts the checks in the project. Its language templates expose the same small set of commands, backed by each language's tools. The Bun template, for example, combines formatting, type checking, and tests behind one entry point.
The trade-off: repair locally, verify in CI
A local check can fix formatting and keep an edit moving. CI needs to judge the submitted code. Harness separates those jobs: check can change files; ci verifies them without applying fixes. The cost is maintaining language-specific runners behind the shared commands.
Harness in practice
Inside a project using the Bun template:
bun run check
bun run ciThe first command runs the local feedback loop. The second checks whether the result meets the project's CI gates.
interlocks
One deterministic Python quality loop for linting, typechecking, tests, coverage, and agent-authored pull requests.
wando
Curated security and privacy recommendations for teams that need practical guidance they can actually follow.
sentinel
URL security analysis tool that traces redirect chains and detects threats to protect users from malicious links.