omni-compression

Solid

Configure RTK (command output), Caveman (prose), and stacked compression modes. Manage language packs, custom rules, and test prompt compression reducing tokens by 60–90%.

AI & Automation 6,067 stars 1058 forks Updated today MIT

Install

View on GitHub

Quality Score: 93/100

Stars 20%
100
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

<!-- generated by src/lib/agentSkills/generator.ts; manual edits will be overwritten --> ## Overview Configure RTK (command output), Caveman (prose), and stacked compression modes. Manage language packs, custom rules, and test prompt compression reducing tokens by 60–90%. ## Authentication All requests require a valid Bearer token or session cookie. Obtain a token via `POST /api/auth/login` or configure `REQUIRE_API_KEY=false` for local development. ## Endpoints ### POST /api/compression/preview Preview compression for a message payload ```bash curl -X POST https://localhost:20128/api/compression/preview \ -H "Authorization: Bearer $OMNIROUTE_TOKEN" -H "Content-Type: application/json" \ -d '{}' ``` ### GET /api/compression/language-packs List Caveman compression language packs ```bash curl https://localhost:20128/api/compression/language-packs \ -H "Authorization: Bearer $OMNIROUTE_TOKEN" ``` ### GET /api/compression/rules List Caveman compression rule metadata ```bash curl https://localhost:20128/api/compression/rules \ -H "Authorization: Bearer $OMNIROUTE_TOKEN" ``` ## Payloads See the full OpenAPI specification at `GET /api/openapi/spec` or `docs/reference/openapi.yaml` for detailed request/response schemas. <!-- skill:custom-start --> <!-- Migrated from skills/omniroute-compression/SKILL.md (preserved curated content) --> # OmniRoute — Compression Requires `OMNIROUTE_URL` and `OMNIROUTE_KEY`. See [entry-point SKILL](https://raw.githubuserconte...

Details

Author
diegosouzapw
Repository
diegosouzapw/OmniRoute
Created
3 months ago
Last Updated
today
Language
TypeScript
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category