Ensemble SOLID review — fans the ruleset across overlapping focused workers over the same code, then reduces by corroboration.
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tessl review fix ./examples/solid-review-ab/multi-low-intelligence-focused-agents/.claude/skills/review-against-solid-principles/SKILL.mdFixed paths (relative to this arm directory, the claude -p working directory):
../ruleset/solid-rules.json*.py under ../corpus/cases/./findings/workers/ (absolute path when calling the planner/workers)./findings/findings.mdplan_ensemble.py and reduce.py from the ensemble-rule-review skill. From this
arm directory they are at ../../../plugins/plugin-creator/skills/ensemble-rule-review/scripts/;
the runner may pass an absolute path instead — use whichever it provides.Plan (deterministic). Run the planner over the shared ruleset, with ./findings/workers/ (as an
ABSOLUTE path) as the report dir:
uv run <scripts>/plan_ensemble.py ../ruleset/solid-rules.json \
--report-dir "$(pwd)/findings/workers" --window 2 --jsonUse the worker assignment and recommended keep-threshold from the planner's output.
Map (parallel). Spawn the principles-reviewer agent once per worker in the plan. Give
each its groups + per-group rules as YOUR RULE SLICE, the identical targets (all files under
../corpus/cases/), and its planner outfile. Run all workers in one parallel batch. Workers
write location as corpus/cases/<file>:<line>.
Reduce (deterministic). Merge by corroboration on (group, location) and write the ranked result
to ./findings/findings.md:
uv run <scripts>/reduce.py "$(pwd)/findings/workers" --glob 'worker-*.md' \
--keep-threshold 2 > ./findings/findings.mdThe reduced, ranked findings in ./findings/findings.md are the arm's output — the scorer parses
them against ../corpus/gold.json.
Each principles-reviewer worker emits the fixed candidate schema.
Jamie-BitFlight/claude_skills
a5218b3
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