Agent skill

Pre Landing Review

by Mathews-Tom in Mathews-Tom/armory

Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage.

MITAuto-check passedDevelopment

Install Pre Landing Review

skills CLI
$ npx skills add Mathews-Tom/armory --skill pre-landing-review -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Mathews-Tom/armory pre-landing-review --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Mathews-Tom/armory.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/pre-landing-review .claude/skills/pre-landing-review && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
pre-landing-review
GitHub stars
329
Token cost
~1.2k tokens
SKILL.md length
533 words
Files
3 (incl. references)
Skills in repo
80
Repo updated
First seen
Licence
MIT

At a glance

Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage.

  • Works in 6 steps: Determine Diff → Load Checklist → Pass 1 — CRITICAL (blocking) → …
  • : is this safe to land
  • SKILL.md covers Workflow and Output
  • Calls git

What it does

Pre Landing Review is an agent skill from Mathews-Tom/armory. Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage. Triggers on: "is this safe to land", "pre-landing review", "safety check before merge", "gate check", "/pre-landing-review". NOT for diff review, use pr-review.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `evals/cases.yaml` and `references/checklist.md`).

It sits in Development, covering Pull requests. It works with SQL. The repository describes itself as: Curated, production-grade skills for AI coding agents. Battle-tested workflows for developers who use AI seriously. The licence is MIT.

When your agent uses it

  • : is this safe to land
  • Pre-landing review
  • Safety check before merge
  • /pre-landing-review

Example prompts

  • “is this safe to land”
  • “pre-landing review”
  • “safety check before merge”
  • “/pre-landing-review”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. Determine Diff
  2. Load Checklist
  3. Pass 1 — CRITICAL (blocking)
  4. Pass 2 — INFORMATIONAL (non-blocking)
  5. Gate Classification
  6. Suppressions

What it can do on your machine

Read from SKILL.md and the folder at commit 4594fb7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Pre Landing Review loads about 1.2k tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 72 tokens; SKILL.md has 533 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Mathews-Tom/armory at commit 4594fb7, republished under its MIT licence (© Mathews-Tom). 533 words, ~1,173 tokens.

Download SKILL.mdSave it as .claude/skills/pre-landing-review/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
pre-landing-review
description
Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage. Triggers on: "is this safe to land", "pre-landing review", "safety check before merge", "gate check", "/pre-landing-review". NOT for diff review, use pr-review.
metadata.version
1.0.1
metadata.category
review
metadata.tags
pre-merge, safety-gate, code-review, checklist
metadata.difficulty
intermediate
metadata.phase
review

Pre-Landing Review

Gate-oriented safety audit for code changes before landing. Uses a structured checklist with two-pass severity triage and blocking/non-blocking classification.

Distinct from pr-review: pr-review is a multi-dimension code quality review. This skill is a gate-oriented safety audit — it uses an external checklist with two-pass severity triage and a blocking/non-blocking classification.

Native alternative: Claude Code's /ultrareview runs a dedicated native review session optimized for bug-finding (Anthropic ships three free per month on Pro/Max plans at Opus 4.7's launch). Use this skill for checklist-driven, gate-oriented blocking classification with a documented triage protocol; use /ultrareview for lightweight bug-hunting on a single change.

Workflow

1. Determine Diff

Identify the changes to review:

  • If on a feature branch: diff against the default branch (git symbolic-ref refs/remotes/origin/HEAD)
  • If given a PR number: fetch that PR's diff
  • If given specific files: review those files
2. Load Checklist

Read references/checklist.md. This is mandatory — if the checklist is unreadable, STOP and report the error.

3. Pass 1 — CRITICAL (blocking)

Review the diff against critical safety categories. These are potential ship-blockers.

SQL & Data Safety
  • Raw SQL without parameterization
  • Schema changes without migration safety (lock timeout, reversibility)
  • Bulk updates/deletes without WHERE clause verification
  • Direct column updates bypassing model validations/callbacks
Race Conditions & Concurrency
  • Read-then-write without locking
  • Unique constraint reliance without database-level enforcement
  • Shared mutable state without synchronization
  • Queue/background job idempotency
Trust Boundaries
  • LLM/AI output used in SQL, shell commands, or rendered HTML without sanitization
  • User input reaching privileged operations without validation
  • External API responses used without schema validation
  • Deserialization of untrusted data

For each CRITICAL finding:

  1. Cite exact file and line
  2. Explain the specific risk
  3. Use AskUserQuestion with exactly three options: Fix now / Acknowledge risk / False positive
  4. If "Fix now": make the fix, then re-check
  5. If "Acknowledge": record acknowledgment, continue
  6. If "False positive": record, continue
Show full SKILL.md (233 more words)Show less
4. Pass 2 — INFORMATIONAL (non-blocking)

Review against remaining categories:

Conditional Side Effects — side effects hidden in conditional branches, callbacks triggered by state changes, error handlers silently swallowing failures.

Magic Numbers — unexplained numeric literals, hardcoded thresholds without constants, timeout values without rationale.

Dead Code — unreachable branches, unused imports, commented-out code without explanation.

Test Gaps — new code paths without test coverage, modified behavior without updated tests, missing edge case and error path tests.

Crypto & Entropy — weak random sources for security contexts, hardcoded secrets, missing TLS/encryption for sensitive data in transit.

Time Window Safety — timezone-naive comparisons, daylight saving edge cases, cron expressions not accounting for clock skew.

Type Coercion — implicit type conversions that could lose data, numeric precision loss across boundaries, implicit string encoding at I/O boundaries.

Present all informational findings in a single summary table (file, line, category, description).

5. Gate Classification
  • All Pass 1 issues resolved (fixed or acknowledged) → CLEAR TO LAND
  • Any unresolved Pass 1 issue → BLOCKED
  • Pass 2 issues are advisory — they don't block landing
6. Suppressions

Do NOT flag:

  • Test files using test fixtures/factories
  • Migration files following framework conventions
  • Comments explaining why a pattern is intentional
  • Configuration files with documented values
  • Type stubs or interface definitions

Output

Gate verdict (CLEAR TO LAND / BLOCKED), critical issues summary with resolution status, informational findings table.

This skill is read-only by default — only modifies code when user explicitly chooses "Fix now" on a critical issue.

© Mathews-Tom, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/pre-landing-review of Mathews-Tom/armory.

  • SKILL.md
  • evals/cases.yaml
  • references/checklist.md

Open the folder on GitHubat commit 4594fb7

Compare with similar skills

Pre Landing Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Pre Landing Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Pre Landing Review this skillMathews-Tom/armory329—~1.2kAutomated safety check: PassMIT
Review PRapache/shardingsphere21k—~6.5kAutomated safety check: PassApache-2.0
Citus Merge Loopcitusdata/citus13k—~2.5kAutomated safety check: PassAGPL-3.0
SeekDB Code Reviewoceanbase/seekdb3.1k—~2.1kAutomated safety check: PassApache-2.0
Mariadb Operator Commentmariadb-operator/mariadb-operator1k—~2.2kAutomated safety check: PassApache-2.0
PR Bot Reviewspgplex/pgconsole155—~2.1kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Pre Landing Review

What does Pre Landing Review do?

Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage. Pre Landing Review is an agent skill from Mathews-Tom/armory. Gate-oriented safety audit for code changes before landing, using a checklist with two-pass severity triage.

When should I use Pre Landing Review?

Pre Landing Review fits situations like: : is this safe to land; pre-landing review; safety check before merge; /pre-landing-review.

How do I install Pre Landing Review in Claude Code?

Run `npx skills add Mathews-Tom/armory --skill pre-landing-review -a claude-code`. Or copy the skill folder (skills/pre-landing-review in Mathews-Tom/armory) into .claude/skills/pre-landing-review in your project. Claude Code loads it when a task matches its description.

How do I install Pre Landing Review in Codex?

Run `npx skills add Mathews-Tom/armory --skill pre-landing-review -a codex`. Or copy the skill folder (skills/pre-landing-review in Mathews-Tom/armory) into .agents/skills/pre-landing-review in your project. Codex loads it when a task matches its description.

Can I use Pre Landing Review in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Mathews-Tom/armory --skill pre-landing-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/pre-landing-review, .gemini/skills/pre-landing-review, .github/skills/pre-landing-review and .opencode/skills/pre-landing-review in your project.

What does Pre Landing Review need to run?

Going by SKILL.md and its folder, Pre Landing Review needs the command-line tools its instructions call (git).

Does Pre Landing Review access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Pre Landing Review safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Pre Landing Review use?

Pre Landing Review is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Pre Landing Review use?

About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 752 tokens, read only when the agent opens those files.

What are the alternatives to Pre Landing Review?

Skills that share tags, products or a category with Pre Landing Review: Review PR (apache/shardingsphere, 21k stars), Citus Merge Loop (citusdata/citus, 13k stars), SeekDB Code Review (oceanbase/seekdb, 3.1k stars) and Mariadb Operator Comment (mariadb-operator/mariadb-operator, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Pre Landing Review?

Mathews-Tom (a GitHub user) maintains it in Mathews-Tom/armory, which has 329 GitHub stars. The repository holds 80 skills in this directory. The repository was last updated on October 6, 2026.

Source: Mathews-Tom/armory on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.