A workflow for taking a pull request—the proposed set of code changes submitted for review—from review to merge. It checks conflicts, automated tests, review comments, and the final squash merge.

Use it to shepherd a pull request through conflict resolution, CI checks, review follow-up, and squash-merging into the main branch.

It keeps you from having to repeatedly check whether a pull request is ready. When checks fail or conflicts appear, it guides the required fixes before merging.

land — Skill by openai

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add skills/openai/symphony/land

Any agent

npx skills add openai/symphony --skill land

Clone the repo

git clone --depth 1 https://github.com/openai/symphony

Made for: Claude Code, Codex.

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,409 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00038	$0.02409
Opus 5	$0.00019	$0.01205
Sonnet 5	$0.00008	$0.00482
Haiku 4.5	$0.00004	$0.00241

Measured 3d ago against content hash 64b5b6e1c613, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

land scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (land_watch.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

land — 100% identical, 2 lines differ
land — 100% identical, 2 lines differ

.codex/skills/land/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Land

Goals

Ensure the PR is conflict-free with main.
Keep CI green and fix failures when they occur.
Squash-merge the PR once checks pass.
Do not yield to the user until the PR is merged; keep the watcher loop running unless blocked.
No need to delete remote branches after merge; the repo auto-deletes head branches.

Preconditions

gh CLI is authenticated.
You are on the PR branch with a clean working tree.

Steps

Locate the PR for the current branch.
Confirm the full gauntlet is green locally before any push.
If the working tree has uncommitted changes, commit with the commit skill and push with the push skill before proceeding.
Check mergeability and conflicts against main.
If conflicts exist, use the pull skill to fetch/merge origin/main and resolve conflicts, then use the push skill to publish the updated branch.
Ensure Codex review comments (if present) are acknowledged and any required fixes are handled before merging.
Watch checks until complete.
If checks fail, pull logs, fix the issue, commit with the commit skill, push with the push skill, and re-run checks.
When all checks are green and review feedback is addressed, squash-merge and delete the branch using the PR title/body for the merge subject/body.
Context guard: Before implementing review feedback, confirm it does not conflict with the user’s stated intent or task context. If it conflicts, respond inline with a justification and ask the user before changing code.
Pushback template: When disagreeing, reply inline with: acknowledge + rationale + offer alternative.
Ambiguity gate: When ambiguity blocks progress, use the clarification flow (assign PR to current GH user, mention them, wait for response). Do not implement until ambiguity is resolved.
- If you are confident you know better than the reviewer, you may proceed without asking the user, but reply inline with your rationale.
Per-comment mode: For each review comment, choose one of: accept, clarify, or push back. Reply inline (or in the issue thread for Codex reviews) stating the mode before changing code.
Reply before change: Always respond with intended action before pushing code changes (inline for review comments, issue thread for Codex reviews).

Read the full file on GitHub · 226 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

land_watch.py 19 KB runs code

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

3d ago First seen · 226 lines · 38 tokens per session scan A 64b5b6e1c613

Subscribe to this mod's changes

land is a skill published in the GitHub repository openai/symphony (26,987 stars, last pushed 14d ago), licensed Apache-2.0. It adds 38 tokens to every session and 2,409 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Git and workflow

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