Codex Autoresearch

Skill by ara.so — Daily 2026 Skills collection.

Codex Autoresearch is a Codex skill that runs an autonomous modify→verify→keep/revert loop on your codebase. You describe a measurable goal in one sentence; Codex confirms the plan, then iterates unattended — every improvement stacks in git, every failure reverts automatically — until interrupted or a cap is reached. Inspired by Karpathy's autoresearch concept, generalized beyond ML training to any software metric.

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Installation

Option A — manual copy into your project:

git clone https://github.com/leo-lilinxiao/codex-autoresearch.git
cp -r codex-autoresearch your-project/.agents/skills/codex-autoresearch

Option B — Codex skill installer:

$skill-installer install https://github.com/leo-lilinxiao/codex-autoresearch

The skill lives at .agents/skills/codex-autoresearch/ inside your project. No config file is required before first use.

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How to Activate

Open Codex in your project directory and prefix your goal with $codex-autoresearch:

$codex-autoresearch
I want to get rid of all `any` types in my TypeScript code

Codex will:

1. Scan the repo and infer scope, metric, verify command, and guard command.
2. Present a confirmation summary — reply go (or correct anything).
3. Run the loop unattended until you interrupt it or the goal is met.

You never write config. Codex infers everything.

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Confirmation Flow

Before the loop starts Codex always shows what it found and asks you to confirm. Example exchange:

Codex: I found 47 `any` occurrences across src/**/*.ts.

       Confirmed:
       - Target: eliminate `any` types in src/**/*.ts
       - Metric: `any` count (current: 47), direction: lower
       - Verify: grep + tsc --noEmit as guard

       Need to confirm:
       - Run until all gone, or cap at N iterations?

       Reply "go" to start, or tell me what to change.

You:   Go, run overnight.

Codex: Starting — baseline: 47. Iterating until interrupted.

Up to five confirmation rounds are possible. After that, Codex proceeds.

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The Loop (internals)

PHASE 0: Probe environment (CPU/GPU/RAM/toolchains), check for session resume
PHASE 1: Read context + lessons file from prior run (if any)

LOOP (forever or N times):
  1. Review current state, git history, results log, lessons
  2. Pick ONE hypothesis (apply perspectives, filter by environment)
     -- or N hypotheses if parallel mode is active
  3. Make ONE atomic change
  4. git commit (before verification)
  5. Run verify command  →  did the target metric improve?
     Run guard command   →  did anything else break?
  6. Improved → keep (extract lesson)
     Worse    → approved rollback strategy (git revert)
     Crashed  → fix or skip
  7. Log the result to results log
  8. Health check (disk, git, verify health)
  9. If 3+ discards → REFINE; 5+ → PIVOT; 2 PIVOTs → web search
 10. Repeat. Never stop. Never ask.

The loop runs unbounded unless you say Iterations: N during confirmation.

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Dual-Gate Verification

Two commands serve distinct purposes:

Guard files are never modified by the loop.

Example verify + guard pair for a Python coverage run:

Verify: pytest --cov=src --cov-report=term 2>&1 | grep TOTAL | awk '{print $NF}'
Guard:  python -m mypy src --ignore-missing-imports

Example for TypeScript type cleanup:

Verify: grep -r "any" src --include="*.ts" | wc -l
Guard:  npx tsc --noEmit

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Modes

Codex maps your sentence to one of seven modes automatically — you never pick a mode explicitly.

loop — iterate toward a measurable target (default)

$codex-autoresearch
Improve test coverage in src/ to at least 80%

$codex-autoresearch
Reduce bundle size — it's currently 2.3 MB, get it under 1 MB

plan — turn a vague goal into a validated loop config

$codex-autoresearch
I want to make our API faster but I don't know where to start

Codex will interview you (p95 latency vs throughput? which endpoint?) and produce a ready-to-run loop config.

fix — repair errors until count reaches zero

$codex-autoresearch
pytest is failing, 12 tests broken after the refactor — fix them all

debug — evidence-driven root-cause hunting

$codex-autoresearch
Our API returns 503 randomly under load, no idea why

Each iteration tests one falsifiable hypothesis. Codex presents evidence, not guesses.

security — read-only STRIDE + OWASP audit

$codex-autoresearch
Is this code secure?

ship — readiness verification and release gating

$codex-autoresearch
Ship it

exec — one-shot execution with no loop

$codex-autoresearch
Run the benchmark suite and summarize results

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Inline Configuration (optional)

You can override defaults inline during the confirmation step — no file edits needed:

Example during confirmation:

You:   Go. Iterations: 30, Guard: npm test, Scope: src/api/

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Cross-Run Learning

At the end of each iteration Codex writes a structured lesson to .agents/skills/codex-autoresearch/lessons.md:

Iteration 7 — KEPT
Hypothesis: replace explicit `any` with inferred generic in src/utils/mapper.ts
Change: added <T extends Record<string, unknown>> to mapKeys()
Result: any count 31 → 29
Lesson: Generic constraints on utility functions eliminate clusters of `any` downstream.

On session resume Codex reads this file first. Each new run benefits from prior runs.

To resume an interrupted run:

$codex-autoresearch
Resume

Codex re-reads the lessons file, checks git state, re-establishes the baseline, and continues.

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Parallel Experiments

Request parallel mode during confirmation or at any time:

You:   Go, parallel 4

Codex runs four hypotheses concurrently, keeps the best result, discards the rest. Useful when hypothesis space is large.

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Pivot Protocol

If the loop stalls, escalation happens automatically:

You are never asked for permission during escalation. The loop continues.

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Real Code Examples

Example 1 — TypeScript any elimination (Python verify script)

If you want a custom verify script instead of a one-liner:

# scripts/count_any.py
import subprocess, sys

result = subprocess.run(
    ["grep", "-r", "--include=*.ts", r"\bany\b", "src/"],
    capture_output=True, text=True
)
count = len(result.stdout.strip().splitlines())
print(count)
sys.exit(0)  # always exit 0; the number is what matters

Tell Codex during confirmation:

Verify: python scripts/count_any.py
Guard:  npx tsc --noEmit

Example 2 — pytest coverage loop (Python)

# scripts/coverage_pct.py
import subprocess, re, sys

out = subprocess.check_output(
    ["pytest", "--cov=src", "--cov-report=term", "-q"],
    stderr=subprocess.STDOUT, text=True
)
match = re.search(r"TOTAL\s+\d+\s+\d+\s+(\d+)%", out)
if match:
    print(int(match.group(1)))
    sys.exit(0)
print(0)
sys.exit(0)

$codex-autoresearch
Improve test coverage — target 85%

Verify: python scripts/coverage_pct.py
Guard:  python -m mypy src
Direction: higher
Target: 85
Iterations: 50

Example 3 — bundle size loop (Node.js project)

# scripts/bundle_size.sh
#!/usr/bin/env bash
npm run build --silent 2>/dev/null
du -k dist/bundle.js | awk '{print $1}'

$codex-autoresearch
Reduce our JS bundle size, currently ~2300 KB, target under 900 KB

Verify: bash scripts/bundle_size.sh
Guard:  npm test
Direction: lower
Target: 900

Example 4 — lint warning count (any language)

# scripts/lint_count.sh
#!/usr/bin/env bash
npx eslint src/ --format json 2>/dev/null \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(sum(len(f['messages']) for f in d))"

$codex-autoresearch
Get our ESLint warning count to zero

Verify: bash scripts/lint_count.sh
Direction: lower
Target: 0

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Unattended Runs

For overnight or long runs, ensure Codex CLI approval settings do not interrupt git commit or git revert commands. The simplest option is to run in a disposable or sandboxed repo clone:

git clone . /tmp/autoresearch-sandbox
cd /tmp/autoresearch-sandbox
# launch Codex here with full permissions

Results accumulate in git history. Pull the winning commits back to your main repo when done:

# in your main repo
git fetch /tmp/autoresearch-sandbox main
git cherry-pick <winning-commit-sha>

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Session Artifacts

These files persist across Codex sessions. Delete them to start fresh.

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Troubleshooting

Loop reverts every change:

• Verify command may be returning a non-numeric value. Test it manually: bash -c "<your verify command>" should print a single number.
• Metric direction may be wrong. Confirm Direction: lower or Direction: higher during setup.

Guard fires on unrelated files:

• Narrow scope: Scope: src/specific-module/
• Or tell Codex explicitly: Do not touch tests/ during confirmation.

Session resume picks up wrong baseline:

• Delete session.json to force a fresh baseline: rm .agents/skills/codex-autoresearch/session.json

Parallel mode produces merge conflicts:

• Codex handles this internally via the pivot protocol, but if it gets stuck, reduce parallelism: Parallel: 2

Codex asks questions mid-loop:

• This means a guard crash produced ambiguous output. Pre-empt it by specifying Guard: <command> || true if guard failures should be non-fatal, or by giving Codex fuller sandbox permissions so it can run git commands freely.

Loop hits PIVOT but makes no progress:

• Supply a seed hypothesis during confirmation: Hint: try tree-shaking unused imports first
• Or run plan mode first to produce a richer hypothesis list before switching to loop.

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Quick Reference

# Start a loop
$codex-autoresearch
<your goal in one sentence>

# Resume interrupted run
$codex-autoresearch
Resume

# Bounded run
$codex-autoresearch
<goal> — Iterations: 25

# Parallel hypotheses
$codex-autoresearch
<goal> — Parallel: 4

# Force a mode
$codex-autoresearch fix
pytest has 8 failures, repair them

# Read-only audit
$codex-autoresearch security
Audit src/api/ for injection vulnerabilities