Use when executing system commands, running Nushell scripts, querying system state, or performing OS interactions with structured JSON output.
Resources
3Install
npx skillscat add tao3k/omni-dev-fusion/omnicell Install via the SkillsCat registry.
SKILL.md
OmniCell
OmniCell transforms the Operating System into a structured data source. Instead of parsing raw text from stdout, you receive JSON objects.
Tools
nuShell
Universal shell tool - use for ANY terminal command.
Parameters:
command(string): Any terminal command (auto-detects observe vs mutate)- Examples:
ls -la,cargo test,git status,npm run build - Read:
open config.json(Returns parsed JSON/Dict directly) - List:
ls **/*.py | sort-by size(Returns List[Dict]) - Query:
ps | where cpu > 10
- Examples:
intent(string, optional): Explicitly forceobserveormutatechunked(bool, defaultfalse): Enable chunked delivery for very large payloadsaction(string, optional):startorbatchsession_id(string): Required foraction=batchbatch_index(int, default0): Required batch index foraction=batchbatch_size(int, default28000): Character window per batch
Usage:
<tool_call>{"name": "omniCell.nuShell", "arguments": {"command": "cargo test"}}</tool_call>Chunked mode (large output):
<tool_call>{"name":"omniCell.nuShell","arguments":{"command":"ls **/*","chunked":true}}</tool_call><tool_call>{"name":"omniCell.nuShell","arguments":{"action":"batch","session_id":"abc123","batch_index":1}}</tool_call>Best Practices
- Structured Data First: Always prefer
openovercat. OmniCell automatically parses JSON, YAML, TOML, XML, and CSV into Python dictionaries. - Pipelines: Use Nu pipes (
|) to filter data before it reaches the LLM context.- Bad:
ls -R(returns huge text block) - Good:
ls **/* | where size > 1mb | to json(returns clean data)
- Bad:
- Large Output: For huge results, prefer
chunked=trueand read allbatch_indexvalues instead of truncating content.