dev:dry-run
SkillDev toolsUse when the user wants to smoke-test the evolve pipeline, test tools, or verify the plugin works end-to-end. Also use when the user says 'dry run', 'smoke test', or 'test pipeline'.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the dev:dry-run skill
What this skill tells your AI
The instructions your AI receives, as published by raphaelchristi/harness-evolver in .claude/skills/dev-dry-run/SKILL.md and read by ahel’s review.
Smoke-test the evolve pipeline. Two modes depending on whether LANGSMITH_API_KEY is available.
Resolve Paths
TOOLS="${EVOLVER_TOOLS:-$([ -d "tools" ] && echo "tools" || echo "$HOME/.evolver/tools")}"
EVOLVER_PY="${EVOLVER_PY:-$([ -f "$HOME/.evolver/venv/bin/python" ] && echo "$HOME/.evolver/venv/bin/python" || echo "python3")}"
Check: Online or Offline?
if [ -n "$LANGSMITH_API_KEY" ]; then
echo "MODE: Online (LANGSMITH_API_KEY found)"
MODE="online"
else
echo "MODE: Offline (no LANGSMITH_API_KEY)"
MODE="offline"
fi
Offline Mode (no API key)
Validate tool syntax and argparse consistency:
echo "=== Tool Syntax Check ==="
for f in $TOOLS/*.py; do
python3 -c "import ast; ast.parse(open('$f').read())" 2>&1
if [ $? -eq 0 ]; then echo "OK: $(basename $f)"; else echo "FAIL: $(basename $f)"; fi
done
echo ""
echo "=== Argparse Flags Check ==="
for f in $TOOLS/*.py; do
$EVOLVER_PY "$f" --help > /dev/null 2>&1
if [ $? -eq 0 ]; then echo "OK: $(basename $f) --help"; else echo "FAIL: $(basename $f) --help"; fi
done
echo ""
echo "=== Skill Cross-Reference Check ==="
# Check every tool referenced in evolve skill exists
for TOOL in $(grep -oh '\$TOOLS/[a-z_]*.py' skills/evolve/SKILL.md | sed 's/\$TOOLS\///' | sort -u); do
if [ -f "$TOOLS/$TOOL" ]; then
echo "OK: $TOOL referenced and exists"
else
echo "FAIL: $TOOL referenced in evolve skill but not found"
fi
done
Online Mode (with API key)
Run the full pipeline with a mock agent:
1. Create temp directory with mock agent
TMPDIR=$(mktemp -d)
cat > "$TMPDIR/agent.py" << 'PYEOF'
import json, sys
input_path = sys.argv[1] if len(sys.argv) > 1 else None
if input_path:
with open(input_path) as f:
data = json.load(f)
question = data.get("input", data.get("question", ""))
print(json.dumps({"output": f"Mock answer to: {question}"}))
else:
print(json.dumps({"output": "No input provided"}))
PYEOF
cat > "$TMPDIR/test_inputs.json" << 'JSONEOF'
[
{"input": "What is 2+2?"},
{"input": "Name a color"},
{"input": "What is Python?"}
]
JSONEOF
echo "Mock agent created at $TMPDIR"
2. Run setup
$EVOLVER_PY $TOOLS/setup.py \
--project-name "dry-run-test" \
--entry-point "python3 $TMPDIR/agent.py {input}" \
--framework "unknown" \
--goals "accuracy" \
--dataset-from-file "$TMPDIR/test_inputs.json" \
--output "$TMPDIR/.evolver.json"
3. Run eval
$EVOLVER_PY $TOOLS/run_eval.py \
--config "$TMPDIR/.evolver.json" \
--worktree-path "$TMPDIR" \
--experiment-prefix "dry-run-v001a"
4. Read results
$EVOLVER_PY $TOOLS/read_results.py \
--experiment "dry-run-v001a" \
--config "$TMPDIR/.evolver.json" \
--format markdown
5. Trace insights
$EVOLVER_PY $TOOLS/trace_insights.py \
--from-experiment "dry-run-v001a" \
--output "$TMPDIR/trace_insights.json"
6. Cleanup
rm -rf "$TMPDIR"
echo "Dry run complete. Temp files cleaned up."
Report
Dry Run Results ({MODE} mode):
Tool syntax: {N}/{N} passed
Argparse: {N}/{N} passed
Cross-refs: {N}/{N} passed
{If online: setup/eval/read/trace pipeline: PASS/FAIL}
Signals
- GitHub stars
- 50
- Forks
- 6
- Last commit
- Apr 2026
Advanced
- Catalog kind
- skill
- Gateway key
dev-dry-run- Source
- github.com/raphaelchristi/harness-evolver