codex-upstream-triage

name	codex-upstream-triage
description	Use when scanning latest upstream OpenAI Codex commits, PRs, releases, or changelog entries to decide which items deserve a GitHub bundle, code analysis, upstream-impact classification, site signal, or Publisher handoff evidence.

Decodex Codex Upstream Triage

Use this skill before deep analysis. Its job is to route the deterministic upstream review queue: group upstream Codex commits correctly, identify likely surfaces, and choose the next artifact without deciding final impact.

This is a Decodex repository-development instruction surface, not an installable Decodex plugin skill.

Read Before Triage

• automations/radar/skills/codex-code-analysis/SKILL.md
• automations/radar/skills/codex-release-analysis/SKILL.md

Inputs

• Upstream repository, normally openai/codex
• A time window, release tag, PR number, commit SHA, or changelog URL
• Optional existing Decodex signal or release-delta artifacts

Retrieval Order

Use the lightest source that can answer the triage question:

1. GitHub commit metadata for the upstream commit stream.
2. GitHub PR metadata when a commit maps to a merged PR or a PR number is known.
3. GitHub release-delta or compare metadata when the user asks for a release or prerelease rollup.
4. Upstream changelog or browser observation when the question is about public product framing.

For normal Radar operation, start from upstream_review_queue/v1, scan recent upstream commits first, and resolve each commit back to a PR when possible. A commit list is a queue for understanding and classification, not final evidence.

For release or prerelease work, compare metadata is a rollup index over the commit/PR history already being analyzed. Do not let a release tag displace the underlying commit and PR evidence.

Candidate Ladder

Classify each item as exactly one:

Decision	Meaning	Next step
skip	AI review confirms internal churn with no safe user or Decodex implication.	Keep ledger trace only.
watch	Interesting but too weak, too hidden, or too broad.	Optional upstream_impact/v1 with control_plane_impact = "watch".
bundle	Enough GitHub context exists for code analysis.	Build or reuse a github_change_bundle/v1.
release_review	Release or changelog framing needs comparison against commits and signals.	Use codex-release-analysis.
style_reference	Useful only as style or audience evidence.	Save no technical artifact; use only as optional style context when a separate source-backed publication candidate exists.

Grouping Rules

• Prefer PR-first grouping over individual commit grouping whenever a commit maps to a merged PR.
• Group adjacent commits when they share the same PR, feature area, or release note.
• Do not split a multi-commit PR into separate signals unless the PR clearly ships multiple independently useful user paths.
• Treat sparse release bodies such as a title-only prerelease as an index into commits, not as enough evidence for confirmed claims.

Radar Triggers

Escalate to codex-code-analysis when changed files or release text mention:

• app-server, app-server protocol, remote control, or websocket transport
• plugins, MCP, tool search, browser automation, or Chrome integration
• sandboxing, permissions, approval policy, hooks, or config schemas
• model providers, auth, accounts, or rate-limit behavior
• CLI/TUI behavior visible to a normal Codex user

Escalate to codex-release-analysis when the source is a release, prerelease, app update, or public changelog. For Codex releases and prereleases, summarize from prior commit/PR analysis whenever possible, then use compare data to find gaps.

Record a Publisher angle only after there is technical source evidence. Style references from X must not start a Publisher handoff by themselves.

Output

Return a compact triage note with:

• source URLs and timestamps
• grouped candidate IDs
• triage decision for each group
• why skipped items were skipped
• next skill to use
• confidence limits

Do not draft signal_entry/v1 or control_plane_upgrade_candidate/v1 directly from this skill. Do not treat deterministic queue hints as technical claims. The durable review layer is upstream_review/v1; public and Control Plane artifacts are promotions from that source-backed review.