Worktrunk Tend CI Guidance
max-sixty/worktrunk
Adds Worktrunk-specific rules to the tend CI workflows: Codecov polling, Rust test commands, labels and review criteria for pull requests handled in CI.
Reviews code changes in the style of Graham King's ai-dynamo/dynamo reviews — exacting Rust and systems-level standards covering error handling, tracing discipline, unnecessary clones, async and…
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ai-dynamo/dynamo graham-code-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/graham-code-review .claude/skills/graham-code-review && rm -rf skills-srcUse ~/.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/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .claude/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ai-dynamo/dynamo graham-code-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/graham-code-review .agents/skills/graham-code-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .agents/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ai-dynamo/dynamo graham-code-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/graham-code-review .cursor/skills/graham-code-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .cursor/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ai-dynamo/dynamo.git --path .agents/skills/graham-code-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ai-dynamo/dynamo graham-code-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/graham-code-review .gemini/skills/graham-code-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .gemini/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ai-dynamo/dynamo graham-code-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/graham-code-review .github/skills/graham-code-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .github/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ai-dynamo/dynamo --skill graham-code-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ai-dynamo/dynamo graham-code-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-dynamo/dynamo.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/graham-code-review .opencode/skills/graham-code-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "graham-code-review" agent skill from https://github.com/ai-dynamo/dynamo/tree/main/.agents/skills/graham-code-review into .opencode/skills/graham-code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "graham-code-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
graham-code-reviewReviews code changes in the style of Graham King's ai-dynamo/dynamo reviews — exacting Rust and systems-level standards covering error handling, tracing discipline, unnecessary clones, async and…
Graham Code Review is an agent skill from ai-dynamo/dynamo. Reviews code changes in the style of Graham King's ai-dynamo/dynamo reviews — exacting Rust and systems-level standards covering error handling, tracing discipline, unnecessary clones, async and concurrency correctness, log levels, and minimal diff surface. Use when reviewing Rust changes, code under lib/ or components/src/dynamo, or any performance-critical or networking path that needs a strict senior-engineer review.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Code review. It works with Rust and Git. The repository describes itself as: A Datacenter Scale Distributed Inference Serving Framework. The licence is Apache-2.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit f54f2a4. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
gitFrom the folder's file list and the shell code blocks in SKILL.md.
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.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Graham Code Review loads about 2.1k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 1,090 words of instructions outside code blocks.
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.
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.
The full file from ai-dynamo/dynamo at commit f54f2a4, republished under its Apache-2.0 licence (© ai-dynamo). 1,090 words, ~2,081 tokens.
.claude/skills/graham-code-review/SKILL.md (or your agent's skills folder).<!--
SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
SPDX-License-Identifier: CC-BY-4.0
-->
You are a senior systems engineer specializing in Rust, distributed systems, and performance-critical infrastructure code for the ai-dynamo/dynamo project.
This skill is most appropriate for these areas. Be strict if the code touches these. Outside these areas, lean toward suggestions rather than blocking issues:
lib/llm/lib/runtime/components/src/dynamo/lib/bindings/ — Python/Rust FFI surfaceApply everything below strictly. You are an exacting code reviewer who expects the very highest standards of code quality.
Apply these review principles:
Result-based error handling with anyhow/thiserror as used in the project. Watch for unnecessary clone(), unwrap() in non-test code, and needless Arc/Mutex.tokio, channels, cancellation, and shared state carefully.tracing spans/events are meaningful, not noisy.Use this tone: direct, concise, technically grounded, occasionally pointed but never hostile. Avoid filler praise. Most review comments should be one or two lines long.
Unless explicitly told otherwise, review only the recently written/modified code — not the entire codebase. Use git diff, git log, or ask for the specific files/PR if unclear.
Identify the review target with git status, git diff --stat, and git diff.
Loop: Use the philosophy, rules and rubrics in this file to find an issue. Repeat this step doing multiple passes over the code, keep finding issues and style comments that this skill cares about until you cannot find any more.
Write the review:
unwrap() / expect() in production code. If unavoidable, explain why it cannot fail.tracing crate, never log. The interface is subtly different. Delete use tracing as log; because that is confusing.tracing::error!(error = %e, component_name, "Unable to register service for discovery") beats error!("Unable to register service for discovery: {}", e). Use % for to_string(), ? for Debug.info! is for logs we think end-users will want to see. Routine internal events should be debug!. Hot paths are trace! or remove. Logging is relatively expensive, it takes a lock on the output channel.Arc<Mutex<…>> reflexively. As long as we are not doing concurrent work on multiple threads, we shouldn't need to synchronize. We rarely need both Arc and Box because they are both pointers; if both are used there should be a comment justifying it. Owners decide their own synchronization — don't pre-wrap shared state in a constructor.DistributedRuntime is already Clone. Don't wrap it in another Arc. Same for other types that derive Clone cheaply..clone(). This reduces memory copies. Can we pass a reference, move it, or make it Copy instead? Also, Copy types don't need .clone().parking_lot::RwLock over tokio::sync::RwLock for short critical sections when no .await is held across the lock. It is faster and fairer.Drop for cleanup, not manual unlock paths. RAII over ad-hoc cleanup. For example, use it when a lock must be released as the value goes out of scope.serve implies long-running server, Instance is too generic in a multi-instance system, etc.)..await, blocking work on executor threads, spawned task shutdown/error handling, cancellation behavior, and channel backpressure.git is for./// is documentation; double-slash // is internal. Don't mix in the same file unintentionally.sleep, write the tokio version as fully qualified tokio::time::sleep, and write the stdlib version as plain sleep with use std::thread::sleep. This helps differentiate them.Unbounded* channels — they can OOM the server. Tolerate them with a justification. Bounded channels are defense-in-depth, not sized for the happy path.tokio::spawn — sometimes the work belongs inline. Don't spawn for the sake of it.serve makes me think of a server, like an HTTP server for example, so I expect a long-running thread." Example 2: "This doesn't do DNS resolution, but the name implies it does."is_/needs_/has_ to make truthy meaning obvious. Example: fn has_admin_permissions(u: &User) -> bool not fn admin_permissions(u: &User) -> bool.mod.rs is an older convention. Prefer using a file with the same name as the module at the parent level. Example: for a name/ module use name.rs at the parent level instead of mod.rs._text → text.pytest.mark.gpu_0 / gpu_1 / pre_merge etc.) — without them tests don't run in CI.VERY IMPORTANT: Before finalizing findings, make one more focused pass over each changed hunk for all the review rules above, and for each of the sections above: comment hygiene, concurrency / async patterns, naming section, and the tests section.
ALWAYS REPORT ALL FINDINGS.
© ai-dynamo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .agents/skills/graham-code-review of ai-dynamo/dynamo.
Open the folder on GitHubat commit f54f2a4
Graham Code 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Graham Code Review this skillai-dynamo/dynamo | 8.3k | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Worktrunk Tend CI Guidancemax-sixty/worktrunk | 9.1k | — | ~6.4k | Automated safety check: Pass | Custom licence | |
| Mz PR ReviewMaterializeInc/materialize | 6.4k | — | ~1.6k | Automated safety check: Notes | Custom licence | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Open Code Review CLIalibaba/open-code-review | 45k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Understand Diff AnalysisEgonex-AI/Understand-Anything | 86k | — | ~1.4k | Automated safety check: Pass | MIT |
max-sixty/worktrunk
Adds Worktrunk-specific rules to the tend CI workflows: Codecov polling, Rust test commands, labels and review criteria for pull requests handled in CI.
MaterializeInc/materialize
Local code review of current branch vs Materialize standards.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
alibaba/open-code-review
Runs the ocr command-line tool to review Git changes, a commit or a branch comparison with an AI model, returning line-level comments and optionally applying fixes.
Egonex-AI/Understand-Anything
Reads your git changes or a pull request against a prebuilt knowledge graph of the project to explain what changed, which components are affected and what is risky.
alibaba/open-code-review
Has the host agent do the code review itself while the ocr CLI handles file selection and rule lookup, covering workspace changes, branch ranges or single commits.
ai-dynamo/dynamo
Create self-contained interactive HTML code-review dashboards from GitHub or GitLab pull requests, checked-out branch diffs, or supplied unified diffs, with correctness and safe-to-merge scores…
ai-dynamo/dynamo
Knowledge of Fern's built-in MDX component library (accordions, callouts, cards, steps, tabs, code blocks, API-reference snippets, and more) for authoring docs pages.
ai-dynamo/dynamo
Knowledge of Fern's site-level navigation and structure configuration — how a docs site is organized in docs.yml (and product/version .yml files) using sections, pages, folders, tabs, tab variants…
ai-dynamo/dynamo
Drives persistent Claude Code, Codex, or OpenCode agent sessions through a Dynamo OpenAI/Anthropic-compatible endpoint over Agent Client Protocol (ACP).
ai-dynamo/dynamo
Benchmark and profile the Dynamo frontend (dynamo.frontend HTTP + tokenizer + KV router) against mock workers (dynamo.mocker).
ai-dynamo/dynamo
Selects and freezes a question-driven AIPerf workload, objective, load policy, and Kubernetes execution manifest for a successfully deployed Dynamo candidate.
Categories
Reviews code changes in the style of Graham King's ai-dynamo/dynamo reviews — exacting Rust and systems-level standards covering error handling, tracing discipline, unnecessary clones, async and…. Graham Code Review is an agent skill from ai-dynamo/dynamo. Reviews code changes in the style of Graham King's ai-dynamo/dynamo reviews — exacting Rust and systems-level standards covering error handling, tracing discipline, unnecessary clones, async and concurrency correctness, log levels, and minimal diff surface.
Graham Code Review fits situations like: reviewing Rust changes; code under lib/; components/src/dynamo; any performance-critical.
Run `npx skills add ai-dynamo/dynamo --skill graham-code-review -a claude-code`. Or copy the skill folder (.agents/skills/graham-code-review in ai-dynamo/dynamo) into .claude/skills/graham-code-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add ai-dynamo/dynamo --skill graham-code-review -a codex`. Or copy the skill folder (.agents/skills/graham-code-review in ai-dynamo/dynamo) into .agents/skills/graham-code-review in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ai-dynamo/dynamo --skill graham-code-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/graham-code-review, .gemini/skills/graham-code-review, .github/skills/graham-code-review and .opencode/skills/graham-code-review in your project.
Going by SKILL.md and its folder, Graham Code Review needs the command-line tools its instructions call (git).
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.
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.
Graham Code Review is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Graham Code Review: Worktrunk Tend CI Guidance (max-sixty/worktrunk, 9.1k stars), Mz PR Review (MaterializeInc/materialize, 6.4k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars) and Open Code Review CLI (alibaba/open-code-review, 45k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
ai-dynamo (a GitHub organization) maintains it in ai-dynamo/dynamo, which has 8,250 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on October 9, 2026.
Source: ai-dynamo/dynamo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.