Benchmark Runner

Run the ai-coding-lang-bench benchmark against AILANG, monitor sessions, analyze results, and identify language gaps.

Quick Start

# Run 5 trials with the spec-prompted strategy
/benchmark-runner run ailang/spec 5

# Monitor live sessions
/benchmark-runner monitor

# Analyze results and compare strategies
/benchmark-runner analyze

When to Use This Skill

Invoke this skill when:

• User says "run benchmark", "benchmark AILANG", "run trials"
• User wants to compare prompt strategies
• User wants to analyze benchmark results or find language gaps
• User says "monitor benchmark" or "check trial progress"

Overview

Fork repo: https://github.com/sunholo-data/ai-coding-lang-bench Local path: /Users/mark/dev/sunholo/ai-coding-lang-bench/

The benchmark has Codex implement "MiniGit" (a minimal git clone) in AILANG. It tests:

• v1: init, add, commit, log (11 tests)
• v2: extends v1 with status, diff, checkout, reset (30 tests)

Each trial invokes Codex -p with a prompt + language-specific extra_prompt.

Prompt Strategy Variants

AILANG has 5 variants in benchmark.rb to measure information value of different documentation layers:

AILANG-SYNTAX.md is auto-copied into each trial's working directory for all ailang variants.

Fair comparison: ailang/spec is the most honest comparison to other languages — the syntax file is equivalent to what training data provides for known languages.

Key Metrics

Available Scripts

scripts/run_trials.sh <variant> <count> [start]

Run benchmark trials for a specific AILANG variant.

# Run 5 trials of ailang/spec starting from trial 1
.Codex/skills/benchmark-runner/scripts/run_trials.sh ailang/spec 5 1

# Run 3 trials of ailang (guided) starting from trial 6
.Codex/skills/benchmark-runner/scripts/run_trials.sh ailang 3 6

scripts/analyze_results.sh

Parse results.json and logs to produce a metrics summary table.

.Codex/skills/benchmark-runner/scripts/analyze_results.sh

scripts/compare_strategies.sh

Side-by-side comparison of different prompt strategy variants.

.Codex/skills/benchmark-runner/scripts/compare_strategies.sh

scripts/find_gaps.sh

Parse Codex session JSONL files to identify repeated failed searches — these indicate AILANG language gaps.

.Codex/skills/benchmark-runner/scripts/find_gaps.sh

scripts/monitor_session.sh

Live monitoring of active benchmark sessions (wrapper around monitor.sh in fork repo).

.Codex/skills/benchmark-runner/scripts/monitor_session.sh        # One-shot
.Codex/skills/benchmark-runner/scripts/monitor_session.sh --watch # Auto-refresh

Workflow

1. Run Trials

# Start with 1 trial to verify setup
ruby benchmark.rb --lang ailang/spec --trials 1 --start 1

# Then run batch of 5
.Codex/skills/benchmark-runner/scripts/run_trials.sh ailang/spec 5

2. Monitor Progress

# In another terminal
cd /Users/mark/dev/sunholo/ai-coding-lang-bench
./monitor.sh --watch

3. Analyze Results

.Codex/skills/benchmark-runner/scripts/analyze_results.sh

4. Identify Gaps

.Codex/skills/benchmark-runner/scripts/find_gaps.sh

Output shows repeated failed searches grouped by topic:

exit/exitCode (14 searches across 3 trials)
  - Trial 1 v1: 14 tool calls searching for exit
  - Trial 2 v1: 8 tool calls
  - Trial 3 v1: 2 tool calls (file-based, faster)

:: cons expression (5 searches across 2 trials)
  - Trial 1 v2: tried x :: xs, got error
  - Trial 2 v2: same pattern

5. Create Design Docs for Gaps

For each identified gap, create a design doc:

# Use design-doc-creator skill
.Codex/skills/design-doc-creator/scripts/create_planned_doc.sh m-gap-name v0_10_0

6. Implement Fixes and Re-benchmark

After implementing a gap fix:

1. Rebuild: make quick-install
2. Regenerate: ailang prompt > AILANG-SYNTAX.md (in fork repo)
3. Run trials again with same variant
4. Compare before/after metrics

Data Locations

/Users/mark/dev/sunholo/ai-coding-lang-bench/
  results/
    results.json         # Structured metrics (time, LOC, pass/fail)
    meta.json            # Environment metadata
    report.md            # Upstream report for other languages
  logs/
    minigit-*.json       # Codex cost/tokens per trial
    session-*.jsonl      # Full chat history (thinking, tool calls, errors)
  generated/
    minigit-*/           # Generated AILANG source code + shell wrappers
  AILANG-SYNTAX.md       # Full ailang prompt output (copied to working dirs)
  monitor.sh             # Live session monitor
  benchmark.rb           # Main benchmark runner

Published Baseline Results

See resources/published_results.md for other language results.

Key comparisons:

• Ruby: $0.36, 73s, 40/40 tests
• Python: $0.38, 75s, 40/40 tests
• Haskell: $0.74, 174s, 39/40 tests

Known Issues

1. Trial isolation: generated/ directory from prior trials is visible — Codex may read previous solutions. Clean generated/ between strategy comparisons.
2. Cache warming: Trial 2+ benefits from Codex prompt caching. First trial of a session is always slower.
3. Exit code gap: AILANG has no exit(code) builtin. Design doc at design_docs/planned/v0_10_0/m-exit-code.md.
4. Cons expression gap: :: only works in patterns, not expressions. Design doc at design_docs/planned/v0_10_0/m-cons-expression.md.

Notes

• Regenerate AILANG-SYNTAX.md after language changes: ailang prompt > /path/to/fork/AILANG-SYNTAX.md
• The benchmark uses Codex -p --dangerously-skip-permissions --output-format json
• Each trial costs ~$0.50-$2.00 depending on discovery overhead
• v2 is always faster than v1 because it extends existing code from v1