gs:landing-report

gs:landing-report is a skill for Claude Code, Codex from thanh-abaii/gstack-windows-port. It costs 18 tokens per session (4,026 once invoked), scanned A, a copy of gs:codex, MIT.

A read-only dashboard for a shared coding workspace. It shows which version slots open pull requests claim, which related workspaces have nearly ready changes, and which slot shipping would choose next.

In plain words
What is it for?
Use it to check the release queue, review open pull requests, see nearby work likely to ship soon, and choose the next version slot.
Why use it?
It removes the need to inspect pull requests and parallel workspaces separately when deciding what can be released next. It only reports the current state and does not change anything.

Skill for Claude CodeCodex

Written for Claude Code and Codex: allowed-tools in frontmatter, but also agents/openai.yaml present. Also seen: mentions CLAUDE.md; names the AskUserQuestion tool; built for gstack.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is ../tokyo-v2 feat/dashboard v1.7.1.0 3h ago none ★ active.

Good fit Use it to check the release queue, review open pull requests, see nearby work likely to ship soon, and choose the next version slot.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/thanh-abaii/gstack-windows-port
agentmods
npx agentmods add skills/thanh-abaii/gstack-windows-port/gstack-landing-report

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gs:landing-report

README.md
[![agentmods](https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-landing-report/github.svg)](https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-landing-report)
Your own site
<a href="https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-landing-report"><img src="https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-landing-report/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gs:landing-report

Your own site · 80×15
<a href="https://agentmods.dev/skills/thanh-abaii/gstack-windows-port/gstack-landing-report"><img src="https://agentmods.dev/badge/skills/thanh-abaii/gstack-windows-port/gstack-landing-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 18 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,026 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.04026
Opus 5 $0.00009 $0.02013
Sonnet 5 $0.00004 $0.00805
Haiku 4.5 $0.00002 $0.00403

Measured 9d ago against content hash b62525d4fd61, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

gs:landing-report 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 9d ago.

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

This is a copy

88% identical to gs:codex — 202 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/gstack-landing-report/SKILL.md · 423 lines

How it starts

The opening of the file, as written. The whole thing — 423 lines — stays where its author put it; the contents beside it link to each section on GitHub.

When to invoke this skill

Shows which VERSION slots are currently claimed by open PRs, which sibling Conductor workspaces have WIP work likely to ship soon, and what slot /ship would pick next. No mutations — just a snapshot. Use when asked to "landing report", "what's in the queue", "show me open PRs", or "which version do I claim next".

/landing-report — Version Queue Dashboard

Preamble (run first)

python "bin/gstack-boot.py" --skill landing-report | iex

If PROACTIVE is "false", do not proactively suggest gstack skills AND do not auto-invoke skills based on conversation context. Only run skills the user explicitly types (e.g., /gs:qa, /gs:ship). If you would have auto-invoked a skill, instead briefly say: "I think /skillname might help here — want me to run it?" and wait for confirmation. The user opted out of proactive behavior.

If SKILL_PREFIX is "true", the user has namespaced skill names. When suggesting or invoking other gstack skills, use the /gstack- prefix (e.g., /gstack-qa instead of /qa, /gstack-ship instead of /ship). Disk paths are unaffected — always use $GSTACK_ROOT/[skill-name]/SKILL.md for reading skill files.

If output shows UPGRADE_AVAILABLE <old> <new>: read $GSTACK_ROOT/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running gstack v{to} (just updated!)" and continue.

If WRITING_STYLE_PENDING is yes: You're on the first skill run after upgrading to gstack v1. Ask the user once about the new default writing style. Use AskUserQuestion:

v1 prompts = simpler. Technical terms get a one-sentence gloss on first use, questions are framed in outcome terms, sentences are shorter.

Keep the new default, or prefer the older tighter prose?

Read the full file on GitHub · 423 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.

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.

  1. 9d ago First seen · 423 lines · 18 tokens per session scan A b62525d4fd61

Subscribe to this mod's changes

gs:landing-report is a skill published in the GitHub repository thanh-abaii/gstack-windows-port (35 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 4,026 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to gs:codex, differing in 202 lines, and is treated as a copy.

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