Codex Insights

Generate an evidence-backed Codex usage report from local Codex history. Treat this as the Codex version of Claude Code's /insights: it analyzes how Codex is being used, not just the current repository.

What to produce

Default to a concise Markdown report with these sections:

1. Current Fact: what data sources were found, the time window, and how many

sessions were analyzed.

1. Usage Patterns: recurring task families, repositories, languages, and

interaction shapes.

1. Friction Points: repeated failures, blocked states, excessive retries,

repeated corrections, or unclear handoffs.

1. Workflow Opportunities: skills, scripts, README updates, automations, or

CLAUDE/AGENTS instruction changes that would remove repeated work.

1. Evidence: concrete session ids, file paths, timestamps, commands, or

short sanitized excerpts that support each recommendation.

If the user asks for a quick summary, keep the report short and put the top recommendations first. If they ask for a deep audit, include the JSON artifact path and enough evidence for follow-up inspection.

Data sources

Look for Codex history in this order:

• $CODEX_HOME if set, otherwise ~/.codex
• state_*.sqlite
• session_index.jsonl
• sessions/**/*.jsonl
• archived_sessions/**/*.jsonl
• memories/MEMORY.md and memories/rollout_summaries/ only when the user

asks to connect the report to durable memory or prior audits

Do not read unrelated browser cookies, keychains, shell histories, or project secrets. Codex insight reports should explain local behavior, not extract private credentials.

Use the bundled analyzer first

Prefer the bundled analyzer for the first pass:

python3 <path-to-skill>/scripts/codex_insights.py --limit 30 --out /tmp/codex-insights

Useful options:

python3 <path-to-skill>/scripts/codex_insights.py --codex-home ~/.codex --limit 100 --out /tmp/codex-insights
python3 <path-to-skill>/scripts/codex_insights.py --cwd /Users/zeeland/projects/rudder-oss --limit 30 --out /tmp/codex-insights-rudder
python3 <path-to-skill>/scripts/codex_insights.py --since 2026-06-01 --out /tmp/codex-insights-june

The script writes:

• report.md: a Markdown report you can quote or refine.
• sessions.json: normalized session records and evidence snippets.
• summary.json: aggregate counts and source metadata.

After the script runs, read report.md and inspect sessions.json only for claims that need stronger evidence.

Analysis discipline

• Build a real cohort before judging patterns. Do not infer "latest 30" from

filenames alone if sqlite or index metadata is available.

• Collapse obvious child/reviewer/subagent sessions under a parent workflow

when spawn-edge metadata is available. If it is unavailable, say so and avoid overclaiming.

• Separate raw session counts from root workflow counts. A fanout-heavy review

task can create many sessions without meaning the user needs a new skill.

• Prefer current local evidence over memory summaries. Memory is useful for

context, but the report should say when a fact is memory-derived rather than freshly verified.

• Distinguish Codex-first findings from Claude Code behavior. Do not describe a

Codex skill as a native slash command unless the user is explicitly asking for a conceptual analogy.

• Redact tokens, API keys, bearer headers, cookies, passwords, and long random

secrets in excerpts.

Recommendation rules

Classify each recommendation as one of:

• new-skill: a repeated multi-step workflow is not covered by an existing

skill and would benefit from reusable instructions or scripts.

• skill-optimization: an existing skill triggered or should have triggered,

but repeated corrections show it needs clearer instructions, evals, or helper scripts.

• automation: the workflow is scheduled, repetitive, and has stable inputs or

check criteria.

• repo-doc: the issue is local project knowledge that belongs in README,

AGENTS.md, CLAUDE.md, or equivalent repo instructions.

• no-op: the pattern is one-off, already covered, or not worth encoding.

Be conservative about new skills. Recommend one only when the evidence shows a recurring workflow with stable trigger conditions and reusable execution steps.

When the user wants implementation

If the user asks to create or update a skill based on the report:

1. Use skill-creator or conversation-to-skill when available.
2. Preserve the evidence trail from this report in the new skill's eval prompts

or README notes where appropriate.

1. Keep report artifacts out of commits unless the user asks to save them.

Output template

Use this shape unless the user asks otherwise:

# Codex Insights

Data window: <dates or latest N>
Sources: <paths>
Analyzed: <raw sessions> sessions, <root workflows if known> root workflows

## Current Fact
...

## Usage Patterns
...

## Friction Points
...

## Workflow Opportunities
...

## Evidence
...

Artifacts:
- <report path>
- <json path>