About cli-eval
A CLI skill for creating and running OmniRoute evaluation suites for LLM outputs. It provides live run monitoring, scorecards, model comparisons, and CI-oriented evaluation workflows.
Key features
- 01Create suites with scoring rubrics
- 02Run and monitor evaluations
- 03Inspect per-sample results
- 04View scorecards
- 05Compare model performance
- 06Use scores in CI workflows
Use cases
- 01Score outputs against expected answers
- 02Track a running evaluation in the terminal
- 03Compare models on the same suite
- 04Fail CI when scores miss a threshold
Install
Copy the command and run it in a terminal.
npx skills add https:/ / github.com/ diegosouzapw/ omniroute --skill cli-evalAfter installing, type/cli-evalin Claude Code to confirm it loaded.
Details
From the project READMEOverview
Create and run evaluation suites, watch live benchmark progress, view scorecards, compare model performance, and integrate eval runs with CI workflows from the CLI.
Quick install
npm install -g omniroute # or: npx omniroute
omniroute --version
Subcommands
eval
Example:
omniroute eval
eval suites
Example:
omniroute eval suites
eval list
Example:
omniroute eval list
eval get <suiteId>
Example:
omniroute eval get <suiteId>
eval create
Flags:
--file <path>
Example:
omniroute eval create
eval run <suiteId>
Flags:
-m, --model <id>--combo <name>--concurrency <n>--tag <tag>--watch
Example:
omniroute eval run <suiteId>
eval list
Flags:
--suite <id>--status <s>--since <ts>--limit <n>
Example:
omniroute eval list
eval get <runId>
Example:
omniroute eval get <runId>
eval results <runId>
Flags:
--failed
Example:
omniroute eval results <runId>
eval cancel <runId>
Flags:
--yes
Example:
omniroute eval cancel <runId>
eval scorecard <runId>
Example:
omniroute eval scorecard <runId>
simulate [prompt]
Flags:
--file <path>-m, --model <id>--combo <name>--reasoning-effort <level>--thinking-budget <n>--explain
Example:
omniroute simulate [prompt]
OmniRoute — CLI Evals
Requires the omniroute CLI. See CLI entry-point skill for install + global flags.
What are evals?
Evals are automated test suites that score LLM outputs against expected answers or rubrics. OmniRoute stores suites and run results in its local database.
Eval suites
omniroute eval suites list # List all eval suites
omniroute eval suites list --json # JSON output
omniroute eval suites get <suiteId> # Full suite definition
Create a suite
omniroute eval suites create \
--name "code-quality" \
--rubric "exact-match" \
--samples-file ./samples.jsonl # JSONL: {input, expected_output}
Rubric options: exact-match, contains, llm-judge, regex.
--samples-file format (one JSON object per line):
{"input": "What is 2+2?", "expected_output": "4"}
{"input": "Translate 'hello' to Spanish", "expected_output": "hola"}
Run an eval
omniroute eval suites run <suiteId> \
--model claude-sonnet-4-6 # Run suite against a specific model
omniroute eval suites run <suiteId> \
--model gpt-4o \
--watch # Live TUI progress (EvalWatch)
The run is asynchronous. Use --watch for a live terminal dashboard or poll manually:
RUN_ID=$(omniroute eval suites run <suiteId> --model claude-sonnet-4-6 --output json | jq -r '.id')
omniroute eval get $RUN_ID
Manage runs
omniroute eval list # List all eval runs
omniroute eval list --json
omniroute eval get <runId> # Run details (status, model, score)
omniroute eval results <runId> # Per-sample results
omniroute eval scorecard <runId> # Full scorecard with pass/fail per sample
omniroute eval cancel <runId> # Cancel a running eval
Scorecard output
omniroute eval scorecard <runId> --output json
Response fields per sample:
{
"id": "sample-1",
"score": 0.95,
"passed": true,
"input": "What is 2+2?",
"output": "4",
"expected": "4"
}
Comparing models
Run the same suite against multiple models and compare:
for MODEL in claude-sonnet-4-6 gpt-4o gemini-2.0-flash; do
omniroute eval suites run $SUITE_ID --model $MODEL --output json | jq '{model: .model, score: .score}'
done
CI integration
# Run and fail CI if score drops below threshold
SCORE=$(omniroute eval suites run $SUITE_ID --model claude-sonnet-4-6 --output json | jq -r '.score')
python3 -c "import sys; score=float('$SCORE'); sys.exit(0 if score >= 0.90 else 1)"
Errors
suites createfails withinvalid rubric→ use one of:exact-match,contains,llm-judge,regexsuites runreturnsmodel not found→ verify model ID withomniroute models --search <name>eval getshowsstatus: failed→ checkomniroute logs --search evalfor error detailsscorecardreturns empty results → the run may still berunning; pollomniroute eval get <runId>untilstatusiscompleted