Agent skill

Ieee Reviewer

by CloudWave818 in CloudWave818/ieee-skills

Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates.

MITAuto-check passedAgent Workflows

Install Ieee Reviewer

skills CLI
$ npx skills add CloudWave818/ieee-skills --skill ieee-reviewer -a claude-code

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

GitHub CLI
$ gh skill install CloudWave818/ieee-skills ieee-reviewer --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/CloudWave818/ieee-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ieee-reviewer .claude/skills/ieee-reviewer && 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
ieee-reviewer
GitHub stars
358
Token cost
~682 tokens
SKILL.md length
204 words
Files
42
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates.

  • Works in 9 steps: Read manifest.yaml. → Read every file listed under always_load. → Detect the axes → …
  • Evaluating scope fit
  • SKILL.md covers Routing Protocol, Output Contract and Red Lines
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ieee Reviewer is an agent skill from CloudWave818/ieee-skills. Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates. Use when evaluating scope fit, novelty, validity, data, clarity, compliance, advancement, engineering significance, method soundness, experiment sufficiency, baseline fairness, figure/table quality, formatting risks, rejection risk, major revision strategy, pre-submission readiness, or the quality and specificity of reviewer comments that may be generic, careless…

Its SKILL.md is about 680 tokens, which your agent loads only when the skill is triggered. The skill folder holds 46 other files (for example `agents/openai.yaml`, `manifest.yaml` and `static/core/output-format.md`).

It sits in Agent Workflows, covering Human-in-the-loop approvals. The repository describes itself as: 面向 IEEE 风格论文写作、润色、审稿、实验、图表、LaTeX、引用和论文阅读的 Codex skills。 The licence is MIT.

When your agent uses it

  • Evaluating scope fit
  • Engineering significance
  • Method soundness
  • Experiment sufficiency

Example prompts

  • “/ieee-reviewer”

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Read manifest.yaml.
  2. Read every file listed under always_load.
  3. Detect the axes
  4. State the detected axes in one short line.
  5. Load only the matching fragments and gates.
  6. Review using IEEE gates in this order
  7. Add first-impression checks for figures, tables, formatting, notation, and language.
  8. For review-comment audits, judge observable quality problems rather than accusing a reviewer of using AI.
  9. Return findings ordered by severity.

What it can do on your machine

Read from SKILL.md and the folder at commit ee30fda. 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

Ieee Reviewer loads about 682 tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 204 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~682

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 CloudWave818/ieee-skills at commit ee30fda, republished under its MIT licence (© CloudWave818). 204 words, ~682 tokens.

Download SKILL.mdSave it as .claude/skills/ieee-reviewer/SKILL.md (or your agent's skills folder). This skill also uses 41 other files; get the full folder from GitHub.
name
ieee-reviewer
description
Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates. Use when evaluating scope fit, novelty, validity, data, clarity, compliance, advancement, engineering significance, method soundness, experiment sufficiency, baseline fairness, figure/table quality, formatting risks, rejection risk, major revision strategy, pre-submission readiness, or the quality and specificity of reviewer comments that may be generic, careless, contradictory, or possibly AI-generated.

IEEE Reviewer Router

Use this skill to simulate a strict IEEE-style technical review. The goal is to find rejection risks and actionable fixes, not to flatter the manuscript.

Do not invent reviewer identities or editorial decisions. Review only the supplied manuscript facts and clearly mark missing materials.

Routing Protocol

  1. Read manifest.yaml.
  2. Read every file listed under always_load.
  3. Detect the axes:
    • venue_type: transaction / journal / letter / conference / magazine / generic.
    • review_scope: full-manuscript / abstract-intro / method / experiments / figures-tables / rebuttal-readiness / review-comment-audit.
    • domain: ai-ml / communications / control / signal-processing / power-energy / circuits / robotics / embedded-systems / general-engineering.
    • strictness: quick / standard / harsh.
  4. State the detected axes in one short line.
  5. Load only the matching fragments and gates.
  6. Review using IEEE gates in this order:
    • scope,
    • novelty,
    • validity,
    • data,
    • clarity,
    • compliance,
    • advancement.
  7. Add first-impression checks for figures, tables, formatting, notation, and language.
  8. For review-comment audits, judge observable quality problems rather than accusing a reviewer of using AI.
  9. Return findings ordered by severity.

Output Contract

Default output:

text
Review setup
- Detected axes:
- Assessment boundary:
- Central claim:
- Visible evidence:

Major rejection risks
- [severity] issue -> why it matters -> fix

Technical review
- Scope:
- Novelty:
- Validity:
- Data and experiments:
- Clarity:
- Compliance:
- Advancement:

Presentation and first impression
- Figures/tables:
- Formatting/notation:
- Writing:

Actionable revision plan
1. ...

Likely decision posture
- [bounded, non-editorial assessment]

Use Critical, Major, and Minor severity labels.

Red Lines

Do not claim the editor's final decision.

Do not invent experiments, results, citations, line numbers, figure contents, or reviewer biographies.

Do not turn the review into author rebuttal unless the user asks for ieee-response.

© CloudWave818, 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 41 other files in skills/ieee-reviewer of CloudWave818/ieee-skills.

  • SKILL.md
  • agents/openai.yaml
  • manifest.yaml
  • static/core/output-format.md
  • static/core/stance.md
  • static/core/workflow.md
  • static/fragments/domain/ai-ml.md
  • static/fragments/domain/circuits.md
  • static/fragments/domain/communications.md
  • static/fragments/domain/control.md
  • static/fragments/domain/embedded-systems.md
  • static/fragments/domain/general-engineering.md
  • static/fragments/domain/power-energy.md
  • static/fragments/domain/robotics.md
  • static/fragments/domain/signal-processing.md
  • static/fragments/review_scope
  • … and 26 more

Open the folder on GitHubat commit ee30fda

Compare with similar skills

Ieee Reviewer 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.

Ieee Reviewer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Ieee Reviewer this skillCloudWave818/ieee-skills358—~682Automated safety check: PassMIT
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Darwin Skill Optimizeralchaincyf/darwin-skill6.2k1 repos~4.7kAutomated safety check: PassMIT
Loop Constraints Enforcercobusgreyling/loop-engineering11k1 repos~475Automated safety check: NotesMIT
Ask User QuestionMemTensor/MemOS12k—~1kAutomated safety check: PassApache-2.0
PUA High-Agency Governancetanweai/pua20k—~502Automated safety check: PassMIT

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Categories

Questions about Ieee Reviewer

What does Ieee Reviewer do?

Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates. Ieee Reviewer is an agent skill from CloudWave818/ieee-skills. Review IEEE conference, journal, Transactions, Letters, or magazine manuscripts from a technical reviewer perspective using routed IEEE review gates.

When should I use Ieee Reviewer?

Ieee Reviewer fits situations like: evaluating scope fit; engineering significance; method soundness; experiment sufficiency.

How do I install Ieee Reviewer in Claude Code?

Run `npx skills add CloudWave818/ieee-skills --skill ieee-reviewer -a claude-code`. Or copy the skill folder (skills/ieee-reviewer in CloudWave818/ieee-skills) into .claude/skills/ieee-reviewer in your project. Claude Code loads it when a task matches its description.

How do I install Ieee Reviewer in Codex?

Run `npx skills add CloudWave818/ieee-skills --skill ieee-reviewer -a codex`. Or copy the skill folder (skills/ieee-reviewer in CloudWave818/ieee-skills) into .agents/skills/ieee-reviewer in your project. Codex loads it when a task matches its description.

Can I use Ieee Reviewer 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 CloudWave818/ieee-skills --skill ieee-reviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ieee-reviewer, .gemini/skills/ieee-reviewer, .github/skills/ieee-reviewer and .opencode/skills/ieee-reviewer in your project.

What does Ieee Reviewer need to run?

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

Does Ieee Reviewer 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 Ieee Reviewer 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 Ieee Reviewer use?

Ieee Reviewer 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 Ieee Reviewer use?

About 682 tokens (SKILL.md is roughly 2.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ieee Reviewer?

Skills that share tags, products or a category with Ieee Reviewer: Show Me Your Work Decision Log (cursor/plugins, 10k stars), Darwin Skill Optimizer (alchaincyf/darwin-skill, 6.2k stars), Loop Constraints Enforcer (cobusgreyling/loop-engineering, 11k stars) and Ask User Question (MemTensor/MemOS, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ieee Reviewer?

CloudWave818 (a GitHub user) maintains it in CloudWave818/ieee-skills, which has 358 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on August 12, 2026.

Source: CloudWave818/ieee-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.