opencode-dockerized: Skill for OpenCode

.opencode/config/skills/code-review/SKILL.md

code-review is a skill for OpenCode from mazumba/opencode-dockerized. It costs 73 tokens per session (1,482 once invoked), scanned A, a copy of code-review, MIT.

A code-review workflow that compares changes against a chosen Git starting point and an agreed specification. It checks both the project's coding standards and whether the changes implement the intended behaviour.

In plain words
What is it for?
It helps review a branch, pull request, or work in progress by examining its diff and commits from a fixed commit, branch, or tag.
Why use it?
A review can miss problems when it checks style but not requirements, or requirements but not code quality. This workflow keeps those two checks separate before combining the findings.

Skill for OpenCode

Written for OpenCode: installed under .opencode/. Also seen: mentions subagents.

This is mazumba/opencode-dockerized's own configuration. It tells OpenCode how to work on opencode-dockerized itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything opencode-dockerized configures →

Reuse

Borrowing it

Nothing to install: this file belongs to mazumba/opencode-dockerized. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/mazumba/opencode-dockerized/main/.opencode/config/skills/code-review/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/mazumba/opencode-dockerized

Made for: OpenCode.

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 code-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/mazumba/opencode-dockerized/code-review/github.svg)](https://agentmods.dev/skills/mazumba/opencode-dockerized/code-review)
Your own site
<a href="https://agentmods.dev/skills/mazumba/opencode-dockerized/code-review"><img src="https://agentmods.dev/badge/skills/mazumba/opencode-dockerized/code-review/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 code-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/mazumba/opencode-dockerized/code-review"><img src="https://agentmods.dev/badge/skills/mazumba/opencode-dockerized/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 73 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,482 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 83% 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 $0.00073 $0.01482
Opus 5.5 $0.00029 $0.00593
Sonnet 5.5 $0.00015 $0.00296
Haiku 4.5 $0.00007 $0.00148

Measured 24d ago against content hash fee1bc8480f6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

code-review 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 24d 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

83% identical to code-review — 16 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.

.opencode/config/skills/code-review/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Two-axis review of the diff between HEAD and a fixed point the user supplies:

  • Standards: does the code conform to this repo's documented coding standards?
  • Spec: does the code faithfully implement the agreed spec?

Both axes run as parallel sub-agents so they don't pollute each other's context, then this skill aggregates their findings.

Process

1. Pin the fixed point

Whatever the user said is the fixed point (a commit SHA, branch name, tag, main, HEAD~5, etc.). If they didn't specify one, ask for it.

Capture the diff command once: git diff <fixed-point>...HEAD (three-dot, so the comparison is against the merge-base). Also note the list of commits via git log <fixed-point>..HEAD --oneline.

Before going further, confirm the fixed point resolves (git rev-parse <fixed-point>) and the diff is non-empty. A bad ref or empty diff should fail here, not inside two parallel sub-agents.

2. Identify the spec source

Look for the originating spec, in this order:

  1. A path or spec the user passed as an argument, or a spec/plan already agreed in the current conversation.
  2. A spec file under docs/, specs/, or .scratch/ matching the branch name or feature.
  3. Issue references in the commit messages (#123, Closes #45, GitLab !67, etc.), fetched with gh issue view or glab issue view when the CLI is available and authenticated. If it isn't, ask the user for the issue text instead.
  4. If nothing is found, ask the user where the spec is. If they say there isn't one, the Spec sub-agent will skip and report "no spec available".

3. Identify the standards sources

Anything in the repo that documents how code should be written, such as CODING_STANDARDS.md or CONTRIBUTING.md.

On top of whatever the repo documents, the Standards axis always carries the smell baseline below: a fixed set of Fowler code smells (Refactoring, ch.3) that applies even when a repo documents nothing. Two rules bind it:

  • The repo overrides. A documented repo standard always wins; where it endorses something the baseline would flag, suppress the smell.
  • Always a judgement call. Each smell is a labelled heuristic ("possible Feature Envy"), never a hard violation. Like any standard here, skip anything tooling already enforces.

Read the full file on GitHub · 86 lines

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. 24d ago First seen · 86 lines · 73 tokens per session scan A fee1bc8480f6

Subscribe to this mod's changes

code-review is a skill published in the GitHub repository mazumba/opencode-dockerized (6 stars, last pushed 2d ago), licensed MIT. It adds 73 tokens to every session and 1,482 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 83% identical to code-review, differing in 16 lines, and is treated as a copy.

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