Skillier

Skillier is a routing skill for AI clients like Claude Desktop, Claude Code, and OpenClaw that gives your AI on-demand access to a curated library of expert skills. Install it once, make a request as usual, and Skillier searches its index, surfaces the top 3–5 matches, and lets you activate the ones you want — loading their instructions directly into context. The project is currently in free early access, with a Lite edition that is MIT-licensed and fully open source.

What It Is

Skillier sits between you and your AI client as a single installed skill that acts as a skill router. Rather than writing custom prompts or maintaining a library of instructions yourself, you activate Skillier and it handles discovery: it matches your natural-language request against a curated databank of expert skill cards spanning finance, design, DevOps, legal, writing, ML, and more. The matched skills are presented as candidates — you confirm which ones load, and the AI follows their instructions for the rest of the turn. Nothing activates automatically; every load requires your explicit confirmation via AskUserQuestion.

Two Editions: Lite and Full

Skillier ships in two distinct editions:

• Skillier Lite — the open-source, local-only edition. It bundles 1,852 curated skills in a ~7 MB .skill file, uses pure stdlib BM25 (Robertson-Sparck-Jones) for ranking, makes no network calls, and has no telemetry. It is MIT licensed and free forever.
• Skillier (Full) — the hosted edition with a backend at api.skillier.ai. It adds BGE-small semantic vectors fused with BM25 via Reciprocal Rank Fusion, an opt-in cross-encoder reranker (Xenova/ms-marco-MiniLM-L-6-v2), and telemetry-driven pick boosting. The full client automatically falls back to the local Lite BM25 index when the backend is unreachable. The full edition's source is not open; it is distributed as a prebuilt bundle.

How the Skill Index Is Built

The Lite databank indexes 1,852 skills across 18 upstream open-source repositories, including sources from Anthropic, Trail of Bits, Vercel Labs, and community contributors. After deduplication (same name + description across sources), cross-source fork filtering, and a curation gate, the result is packed into a single skillbank.jsonl file with a precomputed BM25 inverted index. Each entry carries a source field for attribution. The full hosted index extends this to approximately 4,000 skills with semantic search layered on top.

Security Model

Because skill bodies become in-band instructions for the AI, Skillier treats all skill content as untrusted. The ingest pipeline strips invisible Unicode characters — including Tag block codepoints (U+E0000–E007F), zero-width characters, bidirectional overrides, and variation selectors — that could be used to hide prompt-injection instructions from a human reviewer. A check_invisible.py script can be wired as a pre-commit hook. The sanitizer and its test suite are open source in the repository. Low-substance and near-duplicate skills are filtered out at curation time to keep the index signal-dense.

Update: Skillier v1.5.0

The latest release is v1.5.0, published on 2026-05-30. The GitHub repository was created in May 2026 and shows active development, with the most recent push on 2026-05-30. The release renames bundle assets — current releases use skillier-lite.* for the Lite edition and skillier.* for the full edition, reversing the naming convention used in v1.4.0 and earlier. The project is described as being in free early access for the hosted full edition.