Agent skill

Agent Work Reviewer Maintainer

by Undertone0809 in Undertone0809/rudder

A skill your agent uses when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope…

Apache-2.0Auto-check passedDevelopment

Install Agent Work Reviewer Maintainer

skills CLI
$ npx skills add Undertone0809/rudder --skill agent-work-reviewer-maintainer -a claude-code

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

GitHub CLI
$ gh skill install Undertone0809/rudder agent-work-reviewer-maintainer --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/Undertone0809/rudder.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agent-skills-bak/maintainer/agent-work-reviewer-maintainer .claude/skills/agent-work-reviewer-maintainer && 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
agent-work-reviewer-maintainer
GitHub stars
292
Token cost
~7k tokens
SKILL.md length
3,861 words
Files
2 (incl. references)
Skills in repo
30
Repo updated
First seen
Licence
Apache-2.0

At a glance

A skill your agent uses when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope…

  • Works in 11 steps: Identify The Target → Collect Task Intent → Read Product Context → …
  • Reviewing Rudder agent work
  • SKILL.md covers Use When, Do Not Use When, Evidence Packet and First-Principles Review Frame, plus 5 more sections
  • Calls git and rg

What it does

Agent Work Reviewer Maintainer is an agent skill from Undertone0809/rudder. Use when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope, architecture, and handoff trust.

Its SKILL.md is about 7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/runbook.md`).

It sits in Development, covering Proposals and quotes. The repository describes itself as: Open-source local Agent harness for self-improving agent teams: run agents, review work, and turn feedback into reusable skills. The licence is Apache-2.0.

When your agent uses it

  • Reviewing Rudder agent work
  • Agent outcomes for product correctness
  • Evidence quality

Example prompts

  • “/agent-work-reviewer-maintainer”

Workflow steps

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

  1. Identify The Target
  2. Collect Task Intent
  3. Read Product Context
  4. Verify What Was Proven
  5. Assemble The Review Packet
  6. User Job
  7. Product Object Model
  8. Core Loop Impact
  9. Scope Discipline
  10. Behavioral Completeness
  11. Trust And Validation

What it can do on your machine

Read from SKILL.md and the folder at commit 2676a5c. 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
    • rg

    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

Agent Work Reviewer Maintainer loads about 7k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 59 tokens; SKILL.md has 3,861 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~14k

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 Undertone0809/rudder at commit 2676a5c, republished under its Apache-2.0 licence (© Undertone0809). 3,861 words, ~7,038 tokens.

Download SKILL.mdSave it as .claude/skills/agent-work-reviewer-maintainer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
agent-work-reviewer-maintainer
description
Use when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope, architecture, and handoff trust.

Agent Work Reviewer Maintainer

Review completed or in-progress Rudder agent work. This is a reviewer workflow, not an implementation workflow.

The core question is:

Did the agent solve the right product problem, with the right object model, complete behavior, credible validation, and a clean handoff?

Reviewer is not the same role as verifier. Reviewer may inspect the running product when that is needed for judgment, but its durable responsibility is to judge the diff, architecture, scope, test strategy, handoff safety, and the credibility of acceptance evidence. For black-box acceptance of final product behavior, use product-acceptance-verifier-maintainer.

Default to Chinese when the user asks in Chinese. Keep the verdict early and ground every judgment in evidence.

Use When

Use this skill when the user asks to review:

  • a Codex session, Rudder agent run, task, or transcript
  • a local branch, commit, diff, pull request, or implementation
  • a product proposal, plan doc, feature spec, or UI direction
  • a release verification, Desktop install path, npm publish, or canary/stable handoff
  • a screenshot, browser state, visual interaction, or workflow that "feels wrong"

Common trigger phrases:

  • "review 一下 codex session id ..."
  • "as a 专业产品经理 review"
  • "第一性原理思考一下"
  • "作为 reviewer"
  • "这个实现是不是产品上对"
  • "这个 PR 本地跑起来看一下有没有问题"
  • "这次 release 验证做完了吗"
  • "我觉得这个功能之前有,现在没了"

Do Not Use When

Do not use this skill for:

  • fixing the findings during the same reviewer pass, unless the user explicitly asks to implement fixes
  • generic line-by-line code review where product judgment is irrelevant
  • debugging a failed Rudder agent run root cause only; use the run transcript debugging workflow first, then return here for product/workflow judgment
  • summarizing logs without verdict or acceptance criteria

If the user asks to fix findings after the review, switch to normal implementation mode and follow repository validation, commit, and push rules.

Read-Only Guard

Reviewer mode is read-only by default. Do not edit files, stage changes, restore files, commit, push, start destructive cleanup, or "just fix" findings while reviewing unless the user explicitly changes the task from review to implementation.

If the user says "do not implement", "review only", or assigns a reviewer role, that instruction is binding for the whole reviewer pass. Use tools only to inspect evidence.

Direct UI inspection with Browser, Desktop, or Computer Use is still reviewer work when it only observes or exercises low-risk local/dev flows. If a realistic scenario requires mutating Rudder data, prefer an isolated dev org, disposable test records, or an existing preview instance, and report what was created or changed. Do not delete data, publish, submit external communication, install software, change system settings, or perform other risky UI actions without the appropriate user confirmation.

Evidence Packet

Never start with opinion. Build the smallest evidence packet that can support a real judgment.

1. Identify The Target

Resolve what is being reviewed:

  • Codex session id or prefix
  • Rudder run id or transcript
  • PR number or URL
  • branch name, commit hash, staged/unstaged diff
  • plan doc, proposal, screenshot, or browser URL
  • release version, tag, workflow run, npm dist-tag, or Desktop asset set

If the user is vague, infer from current branch, recent commits, open browser state, or named files before asking.

2. Collect Task Intent

For Codex sessions, search:

bash
rg "<session-id-or-prefix>" ~/.codex/session_index.jsonl ~/.codex/sessions ~/.codex/archived_sessions

Extract real user requests and corrections. Ignore injected AGENTS.md, environment context, skill bodies, and system/developer text.

For branches, PRs, commits, or diffs, inspect:

bash
git status --short --branch
git log --oneline --decorate -12
git diff --stat
git diff
git show --stat <commit>
git show <commit>

For commit or session reviews, also compare the changed-file set against the stated task. Classify every surprising file as one of:

  • required for the requested behavior
  • test, docs, or contract evidence for the requested behavior
  • pre-existing unrelated dirty work
  • unrelated change mixed into the reviewed commit or handoff

Unrelated changes mixed into a product fix are review findings, not cleanup details. If they change skills, release state, generated files, dependencies, or broad runtime behavior outside the task, usually treat that as at least a conditional accept blocker until the scope is split or justified.

For PRs, read the PR description, changed files, review comments, and CI status when available.

3. Read Product Context

For most Rudder product work, read only the relevant sections of:

  • doc/product/GOAL.md
  • doc/product/PRODUCT.md
  • doc/product/README.md plus relevant doc/product/domains/**
  • doc/engineering/DESIGN.md for visible UI and interaction work
  • the task's plan doc under doc/plans/ when one exists

For release/Desktop/package work, also use:

  • doc/engineering/RELEASING.md
  • doc/engineering/PUBLISHING.md
  • doc/engineering/DESKTOP.md
  • .github/workflows/release.yml
  • .github/workflows/desktop-release.yml

For database/API behavior, check the cross-layer contract:

  • packages/db
  • packages/shared
  • server
  • ui
4. Verify What Was Proven

Separate "implemented" from "proven".

Also separate author-claimed proof from reviewer-verified proof.

author-claimed proof includes validation listed in the prompt, final handoff text, copied terminal output, screenshots the reviewer did not inspect, and test names the implementer says were run.

reviewer-verified proof includes commands, logs, screenshots, browser/Desktop state, API readbacks, git evidence, CI state, or release surfaces that this reviewer actually inspected during the review pass.

Do not convert author-claimed proof into reviewer-verified proof. It can support the review, but it cannot close a final handoff gap for UI, workflow, release, Desktop, runtime, or product behavior when the reviewer could cheaply verify the real surface.

Record which evidence exists:

  • typecheck, unit tests, build
  • E2E tests or release smoke tests
  • browser or Desktop visual verification
  • screenshots for visible UI
  • packaged Desktop verification for startup, migrations, profile routing, or installer changes
  • npm/GitHub Release/live workflow checks for release tasks
  • commits, pushes, branch state, PR URL, and merge state

Treat timed-out, skipped, or attempted checks as unverified. Do not convert "looked plausible in code" into product proof.

For spawned child reviewers, full-history forks may include the parent agent's prior commands, screenshots, tests, or edits. Treat inherited history and prompt claims as author-claimed proof unless the child reviewer performs or explicitly re-inspects the evidence after the review assignment starts.

When reviewing in-progress work, spawned reviewer child sessions, or a branch with unrelated dirty feature groups, use a mixed-state verdict instead of a binary pass/fail. Examples:

  • accept: no blocking product, behavior, validation, or handoff gaps remain for the requested scope and verdict level.
  • conditional accept: the artifact direction is sound, but merge/handoff is blocked by missing proof, unrelated dirty work, or explicit reviewer follow-up.
  • needs more evidence: the required scenario, diff, source data, or validation is not available enough to judge.
  • reject: the artifact solves the wrong problem or introduces a blocking regression.

Every verdict must declare its level:

  • stage verdict: judges whether the current requirements, proposal, design, implementation slice, or review artifact is good enough to proceed to the next stage.
  • final handoff verdict: judges whether the requested work can be accepted as done, merged, released, or handed to the user with no blocking evidence gap.

Do not let a stage accept read like a final handoff. If terminal product proof, commit/push state, public release evidence, or reviewer follow-up is still missing, the final verdict cannot be accept even when the stage verdict is positive.

For child-reviewer outputs, preserve the parent task boundary. Do not turn the review into implementation and do not judge sibling or unrelated dirty work as part of the artifact unless it affects merge/handoff safety.

4.1 Evidence Freshness Guard

Before writing the verdict, state the evidence baseline being reviewed. This prevents repeated reviewer child sessions from re-judging stale or mismatched artifacts.

Include the relevant subset:

  • target id: session, run, PR, commit, branch, diff, proposal, release, or screenshot
  • git basis: current branch and commit SHA, plus whether the worktree is dirty
  • diff basis: changed files or git diff --stat scope inspected
  • artifact basis: plan/proposal/screenshot/log path and timestamp when relevant
  • validation basis: checks, browser/Desktop evidence, CI, release workflow, or product proof actually inspected
  • proof split: which evidence was author-claimed versus reviewer-verified
  • review round: first pass, delta review, second round, or final review

If a prior reviewer already judged the same target, same git SHA, and same artifact basis, run a delta review against the changed evidence instead of repeating the full review. If there is no changed evidence, say that the prior verdict still applies and name the missing proof instead of producing a fresh confident verdict.

For spawned reviewer or sub-review work, explicitly say which artifact is being reviewed. Do not silently upgrade the scope from "this proposal" or "this diff" to the whole dirty worktree.

4.2 Run The Real Scenario When It Matters

For functional review, UI review, Desktop review, agent-visible workflow review, or workflow-regression review, prefer direct scenario verification over code-only inference:

  • Use Browser for local web targets such as localhost, 127.0.0.1, or file previews when the browser can exercise the path.
  • Use Computer Use for the packaged Rudder Desktop app, native dialogs, update prompts, menus, resident shell behavior, drag/drop, or any flow that is only visible in the local Mac UI.
  • Use API/log/database checks as supporting evidence, not a replacement for the real operator path when the user's question is about behavior.
  • For CLI or runtime-agent changes, ask whether the actor that will use the feature actually exercised it. A realistic proof usually includes a disposable org/issue/agent or equivalent fixture, the actor command or wakeup, persisted issue/run/comment readback, and the terminal app or CLI surface.
  • If the app is not running, start the appropriate local or packaged Rudder path when that is safe and within the review scope. If startup would be expensive or risky, say exactly why the review is limited.
  • When a real scenario is skipped, the verdict should usually be needs more evidence or conditional accept, and the missing scenario must be named.

For user-visible work, do not accept "tests pass" as enough proof when Computer Use or Browser could cheaply verify the actual Rudder interaction. The minimum credible evidence is the observed workflow state plus any relevant logs, API responses, screenshots, or failure messages.

If the reviewer does not personally inspect the rendered or interactive state for a layout-sensitive UI or functional workflow, the final handoff verdict cannot be accept. Use conditional accept for a sound implementation slice, or needs more evidence when the missing scenario is required to judge the change.

For agent-visible or Rudder work, do not accept direct database assertions, unit tests, or docs updates as the whole proof when a realistic actor-run-chain could cheaply exercise the behavior. Missing terminal product proof should usually make the verdict conditional accept or needs more evidence, even if the diff itself looks correct.

If the user explicitly says the reviewer can use Computer Use or Browser to test a real scenario, treat that as part of the review assignment. If direct scenario verification is skipped or blocked, the verdict should normally be conditional accept or needs more evidence, and the missing interaction must be named.

When the work is already in a routed lifecycle that requires acceptance verification, do not let reviewer scenario checks replace the verifier gate. The review should ask whether a distinct verifier result exists, whether it is PASS, FAIL, or QUESTION, and whether the verifier evidence actually matches the user's acceptance criteria. A reviewer can reject or qualify weak verifier evidence, but should not convert a missing or failing verifier pass into final acceptance.

5. Assemble The Review Packet

Before writing the verdict, make the review packet explicit. It should include the relevant subset:

  • target: session, run, PR, branch, commit, diff, proposal, screenshot, release, or browser state
  • evidence baseline: git SHA/branch, dirty state, diff scope, artifact timestamp, and review round when available
  • user intent: original request plus important corrections or constraints
  • changed object: the product/workflow/code object being reviewed
  • evidence inspected: files, diffs, logs, screenshots, docs, plans, tests, CI, browser/Desktop state, release artifacts, or sub-reviewer notes
  • proof split: author-claimed proof versus reviewer-verified proof
  • verifier status: verifier result, evidence packet, and whether acceptance proof was distinct from code review when required
  • validation status: what passed, what failed, what timed out, what was skipped, and what was only inferred
  • product proof status: actor, trigger, system effect, terminal surface, and any seed/mutation records created for the review
  • unresolved evidence gaps: missing screenshots, missing E2E, unchecked downstream consumers, branch/CI uncertainty, or unverified public surfaces

If any packet item needed for a trustworthy judgment is missing, use needs more evidence or conditional accept; do not fill the gap with confidence.

First-Principles Review Frame

Use this frame before writing the verdict.

1. User Job

What real operator or contributor problem was this task supposed to solve? Was the request a symptom of a deeper workflow issue?

Examples:

  • "Move recent views" may really mean navigation history was modeled as content.
  • "Where did my draft issue go" is a lifecycle and recovery problem, not just a sidebar rendering bug.
  • "Calendar blocks are unreadable" is a time-density visualization problem, not a card styling problem.
2. Product Object Model

Identify the object being changed:

  • view or navigation shortcut
  • workflow state
  • draft, issue, goal, project, run, or artifact
  • external source
  • preference or setting
  • release/version/install surface
  • agent memory, instruction, skill, or operating contract

Judge whether the implementation modeled it as the right kind of object. Many Rudder regressions come from treating a workflow state as a static view, a setting as content, or an external source as an imported local object too early.

3. Core Loop Impact

Ask how the work affects Rudder's north-star loop: real agent work completed end to end.

Good changes reduce operator friction, clarify agent state, preserve control, or make review and handoff easier. Weak changes add surface area without making the agent-work loop more controllable.

4. Scope Discipline

Check whether the work:

  • preserved organization scoping and permissions
  • reused existing product concepts instead of inventing new ones
  • removed half-built surface area when deletion was the right product move
  • preserved legacy paperclip* compatibility where required
  • avoided hiding complexity behind vague copy or fake affordances
  • respected the user's explicit corrections during the session
5. Behavioral Completeness

For user-visible work, inspect the important states:

  • empty, normal, long, loading, error
  • direct link, sidebar link, board card, detail page, and modal entry points
  • cross-organization behavior
  • mobile or constrained width when relevant
  • legacy links and previously shipped features

For UI and functional reviews, ask whether the actual rendered or interactive state was seen. Code review alone is not enough for layout-sensitive work, native Desktop behavior, update flows, chat/issue workflows, or any path where the product claim depends on clicks, typing, selection, focus, async state, or cross-page navigation.

Show full SKILL.md (1,529 more words)Show less
6. Trust And Validation

The user is often asking "can I trust this agent work?" Answer that directly.

Look for:

  • validation mismatch: tests pass but do not cover the operator path
  • regression risk: a refactor deleted a previous capability
  • release mismatch: npm, GitHub Release, Desktop assets, tags, and public entry points disagree
  • branch mismatch: work landed somewhere but not on main
  • handoff mismatch: URL exists but screenshot or real flow evidence is missing
  • hygiene mismatch: the implementation artifact is plausible, but unrelated dirty files, child-session duplication, or pending validation means it cannot be safely merged or handed off as complete

Multi-Round Review

When reviewing a proposal, plan, or agent output across multiple rounds, keep a blocker ledger instead of relying on memory or tone.

Use this shape when it is useful:

markdown
Blocker ledger:
| blocker | severity | round-one evidence | revised answer | status |
| --- | --- | --- | --- | --- |
| ... | P1 | ... | ... | resolved / unresolved |

Second-round review must judge each prior blocker explicitly. An accept verdict means no unresolved blockers remain for the requested scope; it does not mean the proposal is fully implemented or validated.

For reviewer-loop orchestration, disclose whether the review used real spawned reviewers or a serial two-role fallback when that distinction affects trust.

Lens-Specific Checks

UI/UX And Design
  • Read doc/engineering/DESIGN.md before judging.
  • Verify rendered states with Browser, screenshot, Desktop shell evidence, or Computer Use against the real packaged app when native behavior matters.
  • For alignment, row rhythm, avatar/text/time centering, truncation, or column-layout reviews, require production-shaped fixture data and measurable proof when practical. Strong evidence includes real agent avatars, long labels or message text, timestamps/action controls, a screenshot, and DOM bounding boxes or centerline deltas for the elements being aligned.
  • Treat visual hierarchy, density, interaction feedback, animation, native app affordances, and copy clarity as product quality, not nitpicks.
  • Check whether menus, hover actions, dialogs, keyboard behavior, and icons match expected Rudder patterns.
  • If no visual evidence exists, the verdict should usually be needs more evidence or conditional accept.
  • If the claimed fix is "aligned" but the proof only uses placeholder data, isolated component tests, or screenshots that hide the relevant avatar, timestamp, action, or long-text state, the verdict should usually be conditional accept until the real row shape is verified.
Functional Workflow Review
  • Reconstruct the user's real scenario as a short workflow, then run it when the local app, preview, or packaged Desktop is available.
  • Prefer scenario steps such as "open Messenger, send a message, approve the proposal, confirm the issue state" over isolated API calls when the behavior is operator-facing.
  • Use API, logs, DB rows, and code paths to explain why the observed behavior happened after the UI behavior is known.
  • If the scenario would mutate shared or production-like data, use a disposable dev record or ask before the risky step. State any mutation in the review packet.
  • A functional verdict should separate observed user behavior from inferred internal correctness.
Release And Desktop
  • Confirm the relevant version, git tag, npm dist-tag, GitHub Release assets, Desktop portable assets, and install command.
  • For Desktop startup, migrations, profile routing, installer assets, or prod-local paths, packaged verification is required before calling it done.
  • A dry-run does not prove public install. Say exactly which platform and command were actually verified.
Git, PR, Branch, And Worktree
  • Confirm where the change landed and whether it was pushed.
  • If the user expected main, verify main contains the commit.
  • Distinguish the user's unrelated dirty work from the reviewed changes.
  • Check commit hygiene: the changed files should match the requested product object, tests/docs for that object, and necessary contracts. Flag mixed unrelated edits, accidental skill renames, version bumps, generated artifacts, or broad dependency churn inside narrow fixes.
  • When reviewing a Codex session, do not rely only on the final summary saying "committed and pushed"; verify the commit or diff when the local repo is available.
  • For PR preview work, check whether the app was started in an isolated worktree and whether the user received a URL plus screenshots when UI changed.
Agent Skill Or Operating Contract Work
  • Check trigger description, expected workflow, bundled references/scripts, and eval prompts.
  • Verify that repo-local development and maintenance skills use the *-maintainer suffix and live under .agents/skills/maintainer/.
  • Check whether the skill preserves the user's actual repeated corrections rather than only encoding generic best practices.
  • Prefer eval prompts drawn from real Rudder tasks.

Output Shape

Keep the review compact. Lead with the verdict.

markdown
结论:conditional accept。

评分:7/10。

证据基础:
- Session/commit/PR: ...
- Inspect: ...
- Validation: ...
- Gaps: ...

这次任务本质上是在解决:...

做对的地方:
- ...

关键缺口:
1. ...
2. ...

必须补的证据:
- ...

Blocker ledger:
- ...

下一步建议:...

Use accept, conditional accept, reject, or needs more evidence.

Only add line-anchored review findings when they are useful. In Codex app contexts, use ::code-comment{...} for concrete file/line findings and keep the line range tight.

Judgment Rules

  • A task can be directionally correct and still not be done.
  • A stage can pass while final handoff is still blocked.
  • Passing typecheck/build does not prove product behavior.
  • A visible UI task is not done without rendered-state evidence.
  • A release task is not done until npm, tags, GitHub Release, Desktop assets, and public install entry points agree for the intended release surface.
  • Multi-message sessions are not automatic failures; they may be intentional product iteration. Treat repeated corrections as evidence of where the review bar should be raised.
  • "Implemented" means code or docs changed. "Accepted" means the right behavior was proven for the relevant user path.
  • Prefer one pragmatic next move over a long wishlist.

Validation Cases

Case: Two-Round Proposal Review

Input: "Review this proposal as Reviewer A. Do not implement." Then later: "Round 2 review. Judge whether this revised proposal resolves your round-one blockers."

Expected behavior: Round one produces a verdict plus blocker ledger. Round two explicitly checks each blocker against the revised proposal and marks it resolved or unresolved before giving the final verdict.

Must not: Edit files, skip the blocker ledger, or say accept without showing why prior blockers were closed.

Case: Functional Review Of A Shipped Workflow

Input: "功能性上 review 一下 reviewer routing,现在是不是产品上对?"

Expected behavior: The review starts from user intent and workflow semantics, then traces every downstream consumer of the relevant object or field, such as attention, filters, wakeups, UI state, and recovery paths. When Rudder is available locally, it also uses Browser or Computer Use to exercise the real operator path or clearly names why live scenario testing was skipped. The verdict separates observed semantic behavior from schema/type correctness.

Must not: Stop after checking schema, route validation, or the obvious happy-path test.

Case: Functional Review With Computer Use

Input: "review 一下最新版 Desktop update 为什么失败,功能上是不是已经好了."

Expected behavior: The review inspects release and code evidence, then uses Computer Use or an equivalent packaged Desktop run to exercise the actual update interaction when safe. It reports the observed app version, update channel, prompt/toast state, and any supporting health/API/log evidence before judging whether the function is proven.

Must not: Call the update flow accepted from release assets or code inspection alone when the packaged Desktop scenario can be tested.

Case: UI Review Without Rendered Evidence

Input: "review 一下这个 UI 改动有没有问题." The diff is available, but no screenshot, browser state, or Desktop state was captured.

Expected behavior: The review can comment on code and likely risks, but the verdict is conditional accept or needs more evidence if layout, dark/light behavior, overflow, hover, dialog, or responsive state matters.

Must not: Call a layout-sensitive UI change fully accepted from code review alone.

Case: Alignment Review With Placeholder Proof

Input: "这里行对齐没有做好. Review the fix." The submitted proof includes a component test with placeholder icons but no real agent avatar, no timestamp, and no browser geometry or screenshot of the production row.

Expected behavior: The review treats the fix as directionally plausible but not fully proven. It asks for production-shaped fixture proof, ideally a browser screenshot plus DOM bounding boxes or centerline deltas for avatar, text, timestamp, and row container.

Must not: Accept the alignment fix as final from placeholder component tests or a cropped screenshot that does not show the elements whose alignment was questioned.

Case: Explicit Review-Only Guard

Input: "Use agent-work-reviewer-maintainer. Review this proposal. Do not implement or edit files."

Expected behavior: The reviewer inspects evidence and returns a verdict, findings, blocker ledger when useful, and next evidence/fix recommendations. It performs no write action.

Must not: Patch files, stage changes, commit, push, or run destructive cleanup.

Case: Author-Claimed UI Proof Is Not Reviewer Proof

Input: "Review this UI workflow. The implementer says Playwright passed and a screenshot was captured, but you have not opened the app or inspected the screenshot yourself."

Expected behavior: The review may use the claimed checks as supporting context, but it labels them as author-claimed proof. If Browser, Computer Use, screenshot inspection, or a current local preview is available, the reviewer either verifies the real UI state or returns conditional accept / needs more evidence for final handoff.

Must not: Give a final accept by repeating the implementer's claimed Playwright, screenshot, or dev-server evidence as if the reviewer personally verified it.

Case: Spawned Reviewer Full-History Contamination

Input: "You are a spawned reviewer. The inherited transcript includes the author's tests, screenshots, and edits before your assignment. Review the current diff."

Expected behavior: The review treats inherited commands and prompt-provided validation as author-claimed proof unless it reruns or re-inspects them after the review task starts. The verdict says exactly which proof was reviewer-verified and which was inherited.

Must not: Count pre-assignment parent commands as reviewer-verified evidence or call a UI workflow fully accepted from inherited proof alone.

© Undertone0809, 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

Files

SKILL.md and 1 other file (references) in agent-skills-bak/maintainer/agent-work-reviewer-maintainer of Undertone0809/rudder.

  • SKILL.md
  • references/runbook.md

Open the folder on GitHubat commit 2676a5c

Compare with similar skills

Agent Work Reviewer Maintainer 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.

Agent Work Reviewer Maintainer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Agent Work Reviewer Maintainer this skillUndertone0809/rudder292—~7kAutomated safety check: PassApache-2.0
Plan ArbiterBuilderIO/skills4.6k—~1kAutomated safety check: PassMIT
Qv Quality Reportingtetherto/qvac685—~1.6kAutomated safety check: PassApache-2.0
Dev Rfcpproenca/dot-skills215—~3.8kAutomated safety check: PassMIT
Triangulate Spec ReviewQoderAI/better-harness2.4k—~614Automated safety check: PassMIT
Python Pep Authorpproenca/dot-skills215—~2.1kAutomated safety check: PassMIT

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More from Undertone0809/rudder

All 30 skills in this repo
  • Conversation To Skill

    Undertone0809/rudder

    Turn the current conversation's workflow into a reusable agent skill.

    292 GitHub stars~3.6k tokensUpdated today
    Auto-check passed
  • A skill your agent uses when starting the current Rudder checkout as a temporary managed local preview with a stable URL, readiness check, logs, stop command, and cleanup path for manual inspection…

    292 GitHub stars~2.1k tokensUpdated today
    Auto-check passed
  • Stop Rudder Dev Maintainer

    Undertone0809/rudder

    A skill your agent uses when the user explicitly asks to stop, restart, kill, or clean Rudder repo-local pnpm dev processes or local dev runtime residue, including “把 pnpm dev 停了”, “重启 dev”, or “清掉…

    292 GitHub stars~1.3k tokensUpdated today
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  • Deep Research

    Undertone0809/rudder

    Conducts enterprise-grade research with multi-source synthesis, citation tracking, and verification.

    292 GitHub stars~1.2k tokensUpdated today
    Auto-check passed
  • A skill your agent uses to audit or clean Rudder worktrees, generated artifacts, logs, caches, and repo-owned processes without deleting active work, user data, or unrelated machine state.

    292 GitHub stars~664 tokensUpdated today
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  • Visualize

    Undertone0809/rudder

    Create safe inline visual explanations in Rudder Chat. An agent skill from Undertone0809/rudder.

    292 GitHub stars~1.8k tokensUpdated today
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Questions about Agent Work Reviewer Maintainer

What does Agent Work Reviewer Maintainer do?

A skill your agent uses when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope…. Agent Work Reviewer Maintainer is an agent skill from Undertone0809/rudder. Use when reviewing Rudder agent work, Codex sessions, PRs, commits, UI, releases, regressions, proposals, or agent outcomes for product correctness, evidence quality, scope, architecture, and handoff trust.

When should I use Agent Work Reviewer Maintainer?

Agent Work Reviewer Maintainer fits situations like: reviewing Rudder agent work; agent outcomes for product correctness; evidence quality.

How do I install Agent Work Reviewer Maintainer in Claude Code?

Run `npx skills add Undertone0809/rudder --skill agent-work-reviewer-maintainer -a claude-code`. Or copy the skill folder (agent-skills-bak/maintainer/agent-work-reviewer-maintainer in Undertone0809/rudder) into .claude/skills/agent-work-reviewer-maintainer in your project. Claude Code loads it when a task matches its description.

How do I install Agent Work Reviewer Maintainer in Codex?

Run `npx skills add Undertone0809/rudder --skill agent-work-reviewer-maintainer -a codex`. Or copy the skill folder (agent-skills-bak/maintainer/agent-work-reviewer-maintainer in Undertone0809/rudder) into .agents/skills/agent-work-reviewer-maintainer in your project. Codex loads it when a task matches its description.

Can I use Agent Work Reviewer Maintainer 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 Undertone0809/rudder --skill agent-work-reviewer-maintainer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-work-reviewer-maintainer, .gemini/skills/agent-work-reviewer-maintainer, .github/skills/agent-work-reviewer-maintainer and .opencode/skills/agent-work-reviewer-maintainer in your project.

What does Agent Work Reviewer Maintainer need to run?

Going by SKILL.md and its folder, Agent Work Reviewer Maintainer needs the command-line tools its instructions call (git and rg).

Does Agent Work Reviewer Maintainer 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 Agent Work Reviewer Maintainer 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 Agent Work Reviewer Maintainer use?

Agent Work Reviewer Maintainer is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agent Work Reviewer Maintainer use?

About 7k tokens (SKILL.md is roughly 28k 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 7.1k tokens, read only when the agent opens those files.

What are the alternatives to Agent Work Reviewer Maintainer?

Skills that share tags, products or a category with Agent Work Reviewer Maintainer: Plan Arbiter (BuilderIO/skills, 4.6k stars), Qv Quality Reporting (tetherto/qvac, 685 stars), Dev Rfc (pproenca/dot-skills, 215 stars) and Triangulate Spec Review (QoderAI/better-harness, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agent Work Reviewer Maintainer?

Undertone0809 (a GitHub user) maintains it in Undertone0809/rudder, which has 292 GitHub stars. The repository holds 30 skills in this directory. The repository was last updated on October 10, 2026.

Source: Undertone0809/rudder on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.