Official agent skill

Maintainer Review

by redis in redis/node-redis

Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality…

OfficialMITAuto-check passedDevelopment

Install Maintainer Review

skills CLI
$ npx skills add redis/node-redis --skill maintainer-review -a claude-code

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

GitHub CLI
$ gh skill install redis/node-redis maintainer-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/redis/node-redis.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/maintainer-review .claude/skills/maintainer-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
maintainer-review
GitHub stars
18k
Token cost
~5.5k tokens
SKILL.md length
3,008 words
Files
3 (incl. references)
Skills in repo
7
Repo updated
First seen
Licence
MIT

At a glance

Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality…

  • Works in 7 steps: Establish the exact remote target → Establish the unmet need and challenge… → Discover competing open PRs proportionally → …
  • Assessing issue validity
  • SKILL.md covers Objective, Workflow and Resource
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Maintainer Review is an agent skill from redis/node-redis, published by the product's own GitHub organization. Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort. Use when assessing issue validity or severity, deciding whether an issue should be prioritized or closed, determining whether a requested feature represents an unmet need rather than a discoverability or usage gap, judging…

Its SKILL.md is about 5.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/evaluation-framework.md`).

It sits in Development, covering Code quality and Pull requests. It works with Redis and GitHub. The licence is MIT.

When your agent uses it

  • Assessing issue validity
  • Deciding whether an issue should be prioritized
  • Determining whether a requested feature represents an unmet need rather than a discoverability
  • Judging whether a PR is worth bringing to mergeable quality

Example prompts

  • “/maintainer-review”

Workflow steps

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

  1. Establish the exact remote target
  2. Establish the unmet need and challenge the proposed solution
  3. Discover competing open PRs proportionally
  4. Use a two-stage evidence flow
  5. Calibrate validity and impact
  6. Apply the maintainer-effort test
  7. Report the decision and action

What it can do on your machine

Read from SKILL.md and the folder at commit bba9381. 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

    No scripts in the folder and no shell commands in SKILL.md.

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

  • Network

    No URLs in SKILL.md.

    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

Maintainer Review loads about 5.5k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 219 tokens; SKILL.md has 3,008 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~219
When it runs · the whole SKILL.md, loaded when a task matches
~5.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~12k

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 redis/node-redis at commit bba9381, republished under its MIT licence (© redis). 3,008 words, ~5,514 tokens.

Download SKILL.mdSave it as .claude/skills/maintainer-review/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
maintainer-review
description
Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort. Use when assessing issue validity or severity, deciding whether an issue should be prioritized or closed, determining whether a requested feature represents an unmet need rather than a discoverability or usage gap, judging whether a PR is worth bringing to mergeable quality, comparing open PRs or alternative designs, separating code quality from repository readiness, or drafting a concise maintainer assessment. When closure, additional evidence, or code changes should be requested, also produce a polite, concise, complete, copy-paste-ready maintainer comment.

Maintainer Review

Objective

Make a maintainer decision, not a generic diff summary. Separate these questions:

  1. Is the claimed behavior real?
  2. What user outcome or constraint exists independently of the reporter's proposed API or fix?
  3. Can supported functionality already achieve that outcome with reasonable composition or configuration?
  4. If a gap remains, is the proposed solution the best design and implementation layer?
  5. Can supported users plausibly reach the gap, and what happens when they do?
  6. Is it important enough to act on now?
  7. If this PR did not already exist, would maintainers choose to open and implement the same work?
  8. For a PR, is this solution worth merging and maintaining?
  9. Can overlapping or stale operations corrupt shared state or clean up resources owned by surviving work?
  10. If competing PRs exist, which single implementation path should maintainers pursue?
  11. What concise maintainer message should communicate closure, an evidence request, or required changes?

Treat an issue's requested field, callback, flag, class, or implementation strategy as a proposed mechanism, not as the accepted requirement. Do not begin by asking how to implement it. First establish either a concrete unmet user outcome or a violated supported contract, then prove that the proposed mechanism is better than the available alternatives.

Lead with the current review state. Use Preliminary assessment while runtime approval or evidence is pending, and Maintainer decision only when the review can be concluded. Use the diff, issue narrative, and contributor effort as evidence, not as proxies for impact.

Workflow

1. Establish the exact remote target
  • Accept a GitHub issue or PR URL as the primary input. Resolve owner, repository, item type, and number before reviewing it.
  • For an issue, read the full report, comments, reproduction, environment, linked material, and maintainer responses.
  • For a PR, inspect the current remote base and head, full patch, commit history when relevant, tests, linked issue, and review discussion. Do not substitute the current local checkout for the remote change.
  • State the claim in one falsifiable sentence. Separate the observed symptom from the proposed cause or fix.
  • Identify the latest released boundary when compatibility or regression claims matter.
  • Verify whether linked evidence matches the PR's exact runtime variant, provider or tool type, triggering condition, and user outcome. A generic issue title, conceptual similarity, or wording such as Related to does not transfer evidence of need to an adjacent extension. If the reported scenario has already been fixed, treat additional variants as new needs requiring their own evidence.

Use read-only GitHub access. On this laptop, do not run gh unless the user explicitly asks in the same turn. A review never authorizes comments, labels, branch changes, pushes, merges, or other remote writes.

2. Establish the unmet need and challenge the proposed solution

Complete this pass before deeply evaluating a proposed implementation and before any positive issue or PR assessment.

First assign one Need evidence status:

  • Demonstrated: The exact scope has a concrete supported scenario, a real-path reproduction, a released compatibility requirement, a violated supported contract, repeated demand, or a broad invariant with a meaningful consequence.
  • Plausible but unproven: The path can exist, but realistic provider behavior, user reach, frequency, consequence, or demand is not established.
  • Already covered: A reasonable supported workflow already satisfies the outcome.
  • Unsupported: The outcome belongs outside the client's public contract or at a Redis-server, adapter, or caller-owned layer.

Only Demonstrated need may receive Merge-worthy as-is or Merge-worthy after focused changes. For Plausible but unproven, prefer Needs evidence or Not worth completing; for Already covered or Unsupported, prefer closure or the relevant simpler alternative.

  1. Restate the desired user outcome without naming the requested API, class, file, option, or implementation. Separate the actual constraint from the reporter's preferred mechanism.
  2. Trace the closest supported ways to achieve that outcome in the current release and current target. Inspect the owning code path, public API, tests, and relevant docs rather than assuming that an unfamiliar capability is missing. Consider configuration, composition, cloning, callbacks, extension points, provider adapters, and caller-owned code.
  3. Determine whether the report shows a capability gap, an ergonomics or discoverability gap, an unsupported use case, or no demonstrated gap. A more convenient spelling is not automatically a missing capability.
  4. Compare the proposed solution against the strongest existing approach and at least one better-design candidate: no code change, clearer documentation or validation, a narrower fix, reuse of an existing abstraction, or enforcement at a more coherent shared boundary.
  5. For each viable approach, compare whether it satisfies the concrete scenario, what new public or internal contract it creates, cross-path consistency, compatibility, and permanent maintenance cost.

Do not treat a test proving that new code can work as evidence that the feature is needed. A sinon spy or stub, a fake socket, a synthetic fixture built with @redis/test-utils, or a new regression test can establish code-path reachability and implementation correctness; it does not by itself establish realistic server behavior, user reach, frequency, practical consequence, or demand.

API symmetry, naming consistency, and parity with an adjacent command, reply type, or output type are design arguments, not evidence of need. Parity may justify work when it removes existing complexity or enforces a broad demonstrated invariant, but adding branches, tests, documentation, or public behavior requires independent practical justification.

If the need is not Demonstrated, inspect the patch only far enough to understand its contract, risk, and maintenance cost. Do not turn implementation defects, missing tests, or documentation gaps into a request-changes recommendation, because those questions become merge-blocking only after the need gate passes. If the report provides no concrete scenario, the existing functionality appears sufficient, or the requested mechanism solves only a hypothetical convenience problem, prefer Needs evidence, Close, Supersede with a simpler alternative, or Not worth completing over designing the requested feature on the reporter's behalf.

An existing workaround may change priority or solution shape, but it does not by itself erase a demonstrated correctness, security, compatibility, or lifecycle defect in supported behavior. Evaluate both the unmet outcome and the violated contract.

3. Discover competing open PRs proportionally

Do this before deeply evaluating a specified PR. A PR URL selects the starting point, not necessarily the entire comparison set.

  • Determine the primary issue from explicit closing keywords, linked issues, timeline/development links, PR body/comments, and the reproduced symptom. State when association is inferred.
  • When an issue is explicitly linked, enumerate all open PRs that address it through cross-references, closing keywords, and development links. Include drafts but label them.
  • When no issue is linked, run a bounded duplicate search using the strongest signals from the title, reproduction, violated invariant, and runtime path.
  • Exclude closed/merged PRs from the active comparison set while using them as history when relevant.
  • Require a shared issue, symptom, violated invariant, or materially overlapping path. A shared package label is not enough.
  • If repository access cannot establish completeness, say so instead of claiming every candidate was found.

Compare candidates on need coverage, runtime correctness, placement, tests, compatibility, complexity, readiness, remaining maintainer work, and reusable pieces. Prefer the best maintainable solution, not the first or smallest diff by default.

4. Use a two-stage evidence flow

Always begin with a desk review. Inspect the real runtime path before judging a change as trivial or meaningful. Check callers, public exports, equivalent streaming/non-streaming or provider/runtime paths, persistence, cleanup, and focused tests. Inspecting test code is part of the desk review; executing tests, imports, examples, reproductions, benchmarks, or service calls is a runtime probe.

Consult AGENTS.md and the docs/ guides (for example client-configuration, clustering, sentinel, pool, RESP, and transactions) for architecture and background, and treat the source under packages/*/lib as the source of truth. Verify every current claim against the remote change, current source, tests, docs, release boundary, and runtime evidence. Do not infer issue status or PR correctness from a guide.

Use this evidence order across the two stages:

  1. Trace the closest existing supported capabilities and determine whether they already satisfy the underlying user outcome.
  2. Inspect existing tests and complete the code-path trace, including the mandatory interleaving and ownership pass when triggered, without executing code.
  3. With explicit user approval, run a focused local reproduction of the exact claim when the desk-review rules below require it.
  4. A comparison with the latest release, base branch, or another known-good control.
  5. A broader runtime matrix only when the maintainer decision remains uncertain and the user approves it.
Stage 1: desk review

Produce an initial result from static evidence before running code:

Mandatory unmet-need and design pass

Before a positive assessment, complete the pass in step 2 and be able to state all of the following from concrete evidence:

  1. The user outcome that current supported behavior cannot achieve, or the supported contract that the reported defect violates.
  2. The closest existing API or composition path and the exact reason it is insufficient.
  3. Why the proposed behavior belongs at the chosen abstraction layer instead of a caller, provider, adapter, validation, documentation, or existing extension point.
  4. Why the proposed permanent contract is better than no code change and the strongest narrower alternative.
  5. What real scenario, compatibility requirement, violated invariant, or repeated demand justifies the maintenance surface.
  6. Whether maintainers would choose to pursue the same work if no contributor had already supplied a patch.

If any answer is missing and could change whether code should exist at all, do not call the issue actionable or the PR merge-worthy. Request only the evidence needed to distinguish a genuine capability gap or contract violation from a usage, discoverability, or solution-design problem. This is a product and architecture evidence gap, not a runtime-probe trigger by itself.

Show full SKILL.md (1,406 more words)Show less
Mandatory interleaving and ownership pass

Run this pass before any positive PR assessment when a patch adds, removes, or reorders cleanup, retry, reconnect, cancellation, listeners, shared promises or tasks, sockets or streams, state flags, or mutable state across an await, callback, event, or deferred completion.

  1. Name each shared resource or state value and the operation that owns it. Include listeners, promises, tasks, connections, streams, locks, caches, state flags, persistence, and telemetry.
  2. Trace at least two overlapping operations, A and B, across every suspension or re-entry point. Check A pending -> B starts -> A fails -> B succeeds, A pending -> B starts -> B fails -> A succeeds, close or cancellation between setup and completion, and a stale completion arriving after newer work.
  3. For every cleanup or rollback, identify the exact attempt and resource generation it is allowed to dispose. Treat unconditional cleanup after a suspension point as a regression candidate until the code proves it cannot tear down newer or surviving work.
  4. Compare base and head for the survivor invariant. Replacing duplicated work with missing handlers, a closed shared resource, reverted state, or a rejected surviving promise is a regression, not a successful cleanup.
  5. Inspect tests for controlled interleavings using deferred promises, callbacks, or events. Require assertions about the surviving operation's observable behavior and final resource state, not only listener counts or individual rejection results.

Do not mark a concurrency-sensitive patch Merge-worthy as-is merely because sequential reconnect, retry, failure, and close tests pass. If the code trace proves an unsafe interleaving, conclude from static evidence and request a focused fix and regression test. If ownership remains ambiguous, keep the result preliminary and request approval for the smallest decisive runtime probe.

  • If the claim or PR is decisively negative from a complete reachable code-path trace, conclude the review without a runtime probe. Examples include an impossible or unsupported path, duplicated existing handling, a demonstrated no-op, a direct compatibility break, or a clearly wrong abstraction. Do not call an ambiguous result negative merely to avoid a probe.
  • If the initial result is positive and there is no unresolved runtime concern, and any triggered interleaving and ownership pass is complete, the desk review may be sufficient for a final maintainer decision. Do not run a probe only to restate evidence that cannot plausibly change the decision.
  • If the initial result is positive but there is any unresolved runtime concern that could plausibly change claim validity, severity, merge-worthiness, required changes, or the preferred competing PR, stop before executing code. Report a Preliminary assessment, name the concern, propose the smallest decisive probe and control, and ask the user for approval to run it.
  • A purely stylistic, documentation, CI-status, or repository-readiness concern does not trigger a runtime probe unless it masks a runtime question.

Do not issue a definitive positive maintainer decision while a decision-relevant runtime concern remains unresolved. If the user declines the probe, keep the result preliminary and state the exact confidence limitation.

Stage 2: approved runtime probe

After explicit approval, run only the smallest probe needed to resolve the stated concern. Exercise the real public or internal path and include a base, release, or known-good control when relevant. Do not stop at a happy-path smoke check when failure behavior determines the decision. Return to the user for separate approval before expanding materially beyond the approved probe.

For latency, timeout, buffering, backpressure, or cleanup, measure an observable elapsed-time or state transition where feasible. Do not assume that a mocked unit test exercises real scheduling or provider behavior. Prefer a local probe first; use an approval-gated live-service probe only when local evidence cannot settle the decision.

Use $runtime-behavior-probe only when the user explicitly invokes it or approves using it for the proposed runtime work. Preserve its environment-variable, live-service, cost, cleanup, and reporting gates. Ordinary maintainer review must not depend on that skill.

For validation, cleanup, retries, interruption, background work, or concurrency:

  • Identify the earliest correct decision point after dynamic inputs are available.
  • List resources acquired before and after it: listeners, promises/tasks, streams, connections, files, locks, caches, state mutations, and telemetry.
  • Exercise failure during construction, connection, validation, execution, and cleanup where applicable.
  • Verify explicit cleanup when failure occurs before normal teardown.
  • Require a negative-path test when a listener, promise, stream, connection, process, or state can remain.

Stop when additional evidence is unlikely to change validity, severity, or maintainer action.

5. Calibrate validity and impact

Read the evaluation framework when validity, severity, or merge value is not immediately clear.

Assess claim validity, realistic reach, consequence, breadth, frequency, recoverability, compatibility, and severity. Keep observed facts separate from inference and name missing evidence that could change the result.

Report the Need evidence status before classifying the need as a capability gap, ergonomics or discoverability gap, unsupported use case, no demonstrated gap, or a defect in supported behavior. Do not assign practical impact to the absence of the requested mechanism when an existing supported workflow already produces the requested outcome. Do not infer practical importance merely from reachability, API asymmetry, or a technically successful patch.

For a PR, make Severity describe the underlying issue or user need. Report patch-induced regression, compatibility, lifecycle, or maintenance risk separately as Patch risk.

Do not speculate about AI authorship or contributor intent. Identify weak reports through objective evidence: no reproduction, unsupported input, impossible path, duplicated handling, a test that does not exercise the claim, or a fix that is a runtime no-op.

6. Apply the maintainer-effort test

Use one code recommendation:

  • Merge-worthy as-is: real need, sound placement, proportionate scope, and adequate tests.
  • Merge-worthy after focused changes: real need and viable direction with bounded corrections.
  • Supersede with a simpler alternative: real need, but a smaller or more coherent fix is preferable.
  • Not worth completing: negligible/unsupported impact, no-op behavior, wrong abstraction, or excessive completion cost.

Merge-worthy as-is and Merge-worthy after focused changes are invalid unless Need evidence is Demonstrated. A bounded set of implementation fixes cannot promote a Plausible but unproven need into a merge-worthy recommendation.

For merge-worthy recommendations, use one repository-readiness status when useful:

  • Ready
  • CI or review pending
  • Rebase or conflict resolution required
  • Blocked

Omit readiness for supersede/not-worth-completing recommendations; CI does not change those code decisions. Do not downgrade sound code only because CI is pending, and do not call a PR ready when semantic changes remain.

For competing PRs, make one portfolio recommendation: choose one, choose one after focused changes, combine exact pieces into one destination, replace all with a simpler approach, or merge none. State what should happen to every active candidate.

Always compare the proposed patch with the strongest existing supported approach and at least one alternative: no code change, validation or documentation, a narrower fix, reuse of an existing helper, or a different layer that enforces the invariant consistently. A review is incomplete if it establishes only that the patch works without establishing why the current product cannot meet the underlying need or violates a supported contract, and why this design is preferable.

7. Report the decision and action

Choose the assessment language from the current user request and governing repository instructions. Maintainer comment drafts remain English.

Use the matching compact report in the evaluation framework. While runtime approval is pending, use its preliminary-assessment variant and end with the approval request instead of presenting a final recommendation. Keep the report decision-oriented, put unexpected/negative evidence first, and use no more than five evidence bullets by default.

For PRs, put Need evidence before the code recommendation. When the need is not Demonstrated, lead with that result, omit repository readiness, and avoid presenting patch fixes as the primary maintainer action.

When existing functionality or a better alternative materially affects the decision, state it explicitly in the evidence and recommendation. Name the exact supported path, what it does and does not cover, and why it is preferable. Do not bury a Not worth completing or Supersede with a simpler alternative conclusion beneath praise for implementation quality.

When recommending closure, more evidence, focused changes, or superseding a PR, append a polite, complete, copy-paste-ready English maintainer comment. Write the comment as plain markdown without blockquote (>) prefixes or other wrapper markers, so it can be pasted verbatim. Include only merge-blocking work in its required-action paragraph. Do not produce a line-by-line review unless requested, equate passing tests with merge-worthiness, or equate a logically correct patch with practical value.

Resource

  • references/evaluation-framework.md contains the severity rubric, evidence checks, lifecycle review, issue dispositions, PR value checks, documentation threshold, competing-PR framework, maintainer-comment guidance, and compact report variants.

© redis, 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 .agents/skills/maintainer-review of redis/node-redis.

  • SKILL.md
  • agents/openai.yaml
  • references/evaluation-framework.md

Open the folder on GitHubat commit bba9381

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Works with

Questions about Maintainer Review

What does Maintainer Review do?

Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality…. Maintainer Review is an agent skill from redis/node-redis, published by the product's own GitHub organization. Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort.

When should I use Maintainer Review?

Maintainer Review fits situations like: assessing issue validity; deciding whether an issue should be prioritized; determining whether a requested feature represents an unmet need rather than a discoverability; judging whether a PR is worth bringing to mergeable quality.

How do I install Maintainer Review in Claude Code?

Run `npx skills add redis/node-redis --skill maintainer-review -a claude-code`. Or copy the skill folder (.agents/skills/maintainer-review in redis/node-redis) into .claude/skills/maintainer-review in your project. Claude Code loads it when a task matches its description.

How do I install Maintainer Review in Codex?

Run `npx skills add redis/node-redis --skill maintainer-review -a codex`. Or copy the skill folder (.agents/skills/maintainer-review in redis/node-redis) into .agents/skills/maintainer-review in your project. Codex loads it when a task matches its description.

Can I use Maintainer 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 redis/node-redis --skill maintainer-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/maintainer-review, .gemini/skills/maintainer-review, .github/skills/maintainer-review and .opencode/skills/maintainer-review in your project.

What does Maintainer Review need to run?

SKILL.md names no scripts, command-line tools or credentials: Maintainer Review is instructions for the agent only.

Does Maintainer Review access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Maintainer 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 Maintainer Review use?

Maintainer 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 Maintainer Review use?

About 5.5k tokens (SKILL.md is roughly 22k 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 6k tokens, read only when the agent opens those files.

What are the alternatives to Maintainer Review?

Skills that share tags, products or a category with Maintainer Review: Creating Description For Gh PR (redis/jedis, 12k stars), Mariadb Operator PR Review (mariadb-operator/mariadb-operator, 1k stars), PR Auto Review (FontWoW/FontWoW.github.io, 158 stars) and Code Review (sortie-ai/sortie, 197 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Maintainer Review?

redis (a GitHub organization, an official publisher) maintains it in redis/node-redis, which has 17,585 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on October 8, 2026.

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