Set up, install, and configure CONFIDE local de-identification — installs Python deps (natasha, scrubadub, phonenumbers, pymorphy2), ensures Ollama + pulls the default qwen2.5:3b model, detects optional llama.cpp, and writes the optimal-default config so confide:anon and confide:red work with zero further config. Everything is local-first; raw text never leaves the machine. Use when the user says "set up confide", "install confide", "configure confide de-id", "confide setup", or "get confide ready".
npx skills add https://github.com/glebis/claude-skills --skill setup
One-shot installer + optimal-default config writer for the CONFIDE local de-identification
toolkit. After running this, confide:anon (redact a transcript) and confide:red (residual
re-identification risk check) work with no further configuration.
Local-first: all detection and redaction run on the user's machine. Readiness checks and
config writing never read, print, or transmit any transcript text or PII — only booleans and
the config path.
Trigger phrasings: "set up confide", "install confide", "configure confide de-id",
"confide setup", "get confide ready to anonymize".
The entrypoint is scripts/setup.py. It imports the shared core (shared/confide_core.py)
for the canonical DEFAULTS — do not redefine preferences here.
python3 skills/setup/scripts/setup.py --check
Prints a ✓/✗ table: Python deps importable (natasha, scrubadub, phonenumbers, pymorphy2),
Ollama reachable (GET ollama_host/api/tags), the anon_model pulled, llama.cpp on PATH
(optional), and whether the config exists. Booleans only — no PII.
python3 skills/setup/scripts/setup.py --install # core deps + ollama pull
python3 skills/setup/scripts/setup.py --install --with-presidio # + optional EN baseline
natasha scrubadub phonenumbers pymorphy2 pymorphy2-dicts-ru "setuptools<81"(setuptools<81 supplies pkg_resources for pymorphy2). Optional presidio-analyzer behind
--with-presidio.
ollama is on PATH, runs ollama pull qwen2.5:3b. python3 skills/setup/scripts/setup.py --write-config # writes only if absent
python3 skills/setup/scripts/setup.py --reconfigure # overwrites with defaults
python3 skills/setup/scripts/setup.py --show # print current config
On first run with no config present, the script writes the defaults automatically.
--write-config will not clobber an existing (user-customized) config; use
--reconfigure to force-reset.
Config lives at ~/.config/confide/config.json.
Written from confide_core.DEFAULTS:
| Key | Value | Why |
|---|---|---|
| engine | ollama | zero-config, Metal-accelerated, handles long docs (llama.cpp 400s on long RU) |
| anon_model | qwen2.5:3b | fast local LLM layer for quasi-PII |
| red_attacker_model | qwen2.5:3b | local default; it is a floor — a stronger attacker is the true ceiling |
| languages | ["ru", "en"] | bilingual corpus |
| layers | ["regex", "natasha", "llm"] | deterministic → RU NER → quasi-PII |
| redaction_style | typed_placeholder | [PERSON], [DATE], … (reversible map kept locally, never shipped) |
| privacy.local_only | true | raw text never leaves the machine |
| privacy.cloud_apis | false | cloud disabled by default |
| privacy.cloud_only_on_synthetic | true | cloud attacker only opt-in on synthetic/consented data |
| ollama_host | http://localhost:11434 | local Ollama |
confide:red is optional; the local 3b default under-reports risk.readiness(), ensure_config(reconfigure=False),install(with_presidio=False), show_config().
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
Next.js best practices - file conventions, RSC boundaries, data patterns, async APIs, metadata, error handling, route handlers, image/font optimization, bundling
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - creates isolated git worktrees with smart directory selection and safety verification
Take glebis/setup from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.