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Use the EVO agent persona (Explicit-assumption Verification Orchestrator) for Prolog-first reasoning that requires explicit assumptions, consistency checks, assumption-dependence testing, and derived conclusions with proof traces. Use when a task needs rigorous stepwise verification rather than a best-effort natural language answer.

machinelearning2014 By machinelearning2014 schedule Updated 3/7/2026

name: evo description: Use the EVO agent persona (Explicit-assumption Verification Orchestrator) for Prolog-first reasoning that requires explicit assumptions, consistency checks, assumption-dependence testing, and derived conclusions with proof traces. Use when a task needs rigorous stepwise verification rather than a best-effort natural language answer.

EVO

What this skill does

  • Defines an EVO subagent persona via agents/openai.yaml with a strict "Prolog-first" verification workflow.
  • Pushes EVO to treat assumptions as explicit objects, run consistency checks, test assumption-dependence, and avoid "from memory" answers.

How to use

  • Ask EVO to solve a problem and require it to use Prolog derivations before stating conclusions.
  • To actually execute Prolog locally, use skills/evo/scripts/evo_run.py, which wraps skills/prolog-runner/scripts/run_prolog.py and embeds the EVO harness from skills/evo/references/evo_harness.pl.
  • For routine runs, keep KB text in memory and pipe to --kb-stdin (do not create temporary *.pl files unless explicitly requested).

Example (default, no KB file creation):

PowerShell: @' observation(example). rule(r1, conclusion(ok), [example]). '@ | python C:\\Users\\trung\\.codex\\skills\\evo\\scripts\\evo_run.py --kb-stdin --assumption some_assumption

Do not use Write/Edit tools to create temporary KB files for routine runs.

Claude default (no temporary .pl file creation):

cat path/to/task.pl | python C:\\Users\\trung\\.claude\\skills\\evo\\scripts\\evo_run.py --kb-stdin --assumption some_assumption

Resources

  • skills/evo/references/evo_harness.pl: minimal harness providing proof tracing, assumptions, and consistency checks.
  • skills/evo/references/template_kb.pl: starter template for task KBs.
  • skills/evo/scripts/evo_run.py: helper to run inconsistent + derive conclusions and do assumption-drop tests.

Tip: prefer --kb-stdin over --kb-file for routine runs, and avoid large inline python -c base64 snippets. Use --kb-file only for explicit file artifacts and --kb-b64 only when stdin piping is unavailable.

Install via CLI
npx skills add https://github.com/machinelearning2014/evo --skill evo
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