A skill your agent uses when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review…

MITAuto-check passed

Install Iros Author Response

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iros-author-response -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills iros-author-response --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/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/IROS-Skills/skills/iros-author-response .claude/skills/iros-author-response && 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
iros-author-response
GitHub stars
1.2k
Token cost
~953 tokens
SKILL.md length
425 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review…

  • Works in 4 steps: Name the gap precisely — 20 trials on 3… → Scope the fix — 120 trials across 15… → Choose the target — RA-L (for revision… → …
  • Responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission
  • SKILL.md covers Channel 1: pre-answer before…, Channel 2: the camera-ready…, Channel 3: RA-L response… and Micro-example: turning a…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Iros Author Response is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review through camera-ready edits, writing RA-L response letters for the journal pathway, and drafting reject-to-ICRA/CoRL/RA-L resubmission memos under double-anonymous rules.

Its SKILL.md is about 950 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. | 覆盖主流期刊的… The licence is MIT.

When your agent uses it

  • Responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission
  • Addressing the meta-review through camera-ready edits
  • Writing RA-L response letters for the journal pathway
  • Drafting reject-to-ICRA/CoRL/RA-L resubmission memos under double-anonymous rules

Example prompts

  • “/iros-author-response”

Workflow steps

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

  1. Name the gap precisely — 20 trials on 3 objects is too thin for the reliability claim.
  2. Scope the fix — 120 trials across 15 objects with a logged failure taxonomy.
  3. Choose the target — RA-L (for revision cycles) or the next ICRA (for the spring deadline).
  4. Decide the video re-cut — add a labeled failure to pre-answer the same objection.

What it can do on your machine

Read from SKILL.md and the folder at commit 932eb23. 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

Iros Author Response loads about 953 tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 425 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~91
When it runs · the whole SKILL.md, loaded when a task matches
~953

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 brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 425 words, ~953 tokens.

Download SKILL.mdSave it as .claude/skills/iros-author-response/SKILL.md (or your agent's skills folder).
name
iros-author-response
description
Use when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review through camera-ready edits, writing RA-L response letters for the journal pathway, and drafting reject-to-ICRA/CoRL/RA-L resubmission memos under double-anonymous rules.

IROS Author Response

Use this after IROS reviews arrive — and, crucially, before submission too, because IROS traditionally offers no rebuttal. The reviews come with the decision, so the "response" is spread across three real channels: pre-answering in the paper, editing the camera-ready, and, if rejected or on the journal route, a response letter or resubmission memo. Confirm the current cycle's policy before assuming a rebuttal window does or does not exist.

Channel 1: pre-answer before you submit

The most effective IROS author response is written before anyone reviews the paper. Anticipate the standard objections and disarm them in the body and the video:

  • "Did it really work?" → shown, uncut trials plus a labeled failure in the video.
  • "Is it reliable or cherry-picked?" → trial counts, resets, and a failure taxonomy in the body.
  • "Does sim imply real?" → a stated sim-to-real gap, not an implied zero.
  • "Is the baseline fair?" → same-platform baseline with comparable tuning.

Channel 2: the camera-ready revision

When the decision is accept (often with requested changes), the meta-review is your instruction set. Integrate its asks without inflating the contribution beyond what was reviewed.

Meta-review askCamera-ready moveTrap to avoid
"Report failure cases"Add the failure taxonomy table you loggedDo not add new claims the reviewers never saw
"Clarify the compute budget"State measured rate and power on the robotDo not quietly change the reported system
"Compare to system X"Add the same-platform comparison if you have itDo not fabricate a comparison you did not run
"Fix anonymized links"Replace with the public, licensed releaseDo not leave "code coming soon"
Show full SKILL.md (160 more words)Show less

Channel 3: RA-L response letters and resubmission memos

  • If your work is on the RA-L journal pathway, that review does have response letters: answer each point, quote the change, and cite the revised line — a very different discipline from the no-rebuttal conference.
  • If the IROS paper is rejected, write a short internal resubmission memo: which objections were evidence gaps (fixable with a run), which were framing, and which venue (next ICRA, CoRL, or RA-L) the revised paper best fits.

Micro-example: turning a rejection into a plan

Reviewers rejected a manipulation paper for "insufficient real-robot evidence." The memo:

  1. Name the gap precisely — 20 trials on 3 objects is too thin for the reliability claim.
  2. Scope the fix — 120 trials across 15 objects with a logged failure taxonomy.
  3. Choose the target — RA-L (for revision cycles) or the next ICRA (for the spring deadline).
  4. Decide the video re-cut — add a labeled failure to pre-answer the same objection.
text
Response draft skeleton (camera-ready or RA-L letter):
  [Point] <reviewer/meta-review concern>
  [Change] <exact edit or added table/figure>
  [Location] <section / table / line in the revised paper>
  [Not added] <new claims deliberately withheld to stay within review scope>

Output format

text
[Channel] pre-submission / camera-ready / RA-L letter / resubmission memo
[Priority concern] <the objection that most threatens acceptance>
[Response] <IROS-appropriate, scoped, anonymity-safe>
[Evidence anchor] <paper/video/log item>
[Forbidden] <new unsupported claims / identity leaks / fabricated comparison>

© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in IROS-Skills/skills/iros-author-response of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Iros Author Response 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.

Iros Author Response compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Iros Author Response this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~953Automated safety check: PassMIT
Responsive Unitsthedaviddias/Front-End-Checklist74k—~472Automated safety check: PassMIT
Author Response Builderaipoch/medical-research-skills1.9k—~3.2kAutomated safety check: PassMIT
Rebuttal ResponseM1n-n9/paper-lifecycle693—~1.9kAutomated safety check: PassNone
Hermes Agent Skill AuthoringNousResearch/hermes-agent252k—~3.6kAutomated safety check: PassMIT
Icsme Author Responsebrycewang-stanford/Awesome-Journal-Skills1.2k—~1.3kAutomated safety check: PassMIT

Similar skills

  • Responsive Units

    thedaviddias/Front-End-Checklist

    A skill your agent uses when reviewing stylesheets, component styles, and responsive behavior related to Use relative units for responsive layouts.

    74k GitHub stars~472 tokensUpdated 4 days ago
    Frontend & DesignAuto-check passed
  • Author Response Builder

    aipoch/medical-research-skills

    Turns reviewer comments into structured, professional point-by-point responses linked to manuscript revisions, clarifications, rebuttals, and additional analyses.

    1.9k GitHub stars~3.2k tokensUpdated 24 days ago
    Research & ScienceAuto-check passed
  • Rebuttal Response

    M1n-n9/paper-lifecycle

    Plan, triage, and write academic rebuttals and review responses.

    693 GitHub stars~1.9k tokensUpdated 3 mo ago
    Research & ScienceAuto-check passed
  • Hermes Agent Skill Authoring

    NousResearch/hermes-agent

    Author in-repo SKILL.md files: frontmatter and structure. An agent skill from NousResearch/hermes-agent.

    252k GitHub stars~3.6k tokensUpdated yesterday
    Agent WorkflowsAuto-check passed
  • Icsme Author Response

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when drafting an IEEE ICSME author response during the double-anonymous author-response period, covering the early-decision cut that decides whether you respond at all…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Fast Author Response

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when drafting USENIX FAST author responses, covering the short pre-notification rebuttal during the author-response period and — distinctively — the one-shot-revision change…

    1.2k GitHub stars~1.5k tokensUpdated 14 days ago
    Auto-check passed

More from brycewang-stanford/Awesome-Journal-Skills

All 2,387 skills in this repo
  • Aaag Data Analysis

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Literature Positioning

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Rebuttal

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…

    1.2k GitHub stars~1.4k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Research Design

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…

    1.2k GitHub stars~1.4k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Review Process

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…

    1.2k GitHub stars~1.3k tokensUpdated 14 days ago
    Auto-check passed
  • Aaag Submission

    brycewang-stanford/Awesome-Journal-Skills

    A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…

    1.2k GitHub stars~1.6k tokensUpdated 14 days ago
    Auto-check passed

Questions about Iros Author Response

What does Iros Author Response do?

A skill your agent uses when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review…. Iros Author Response is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission, addressing the meta-review through camera-ready edits, writing RA-L response letters for the journal pathway, and drafting reject-to-ICRA/CoRL/RA-L resubmission memos under double-anonymous rules.

When should I use Iros Author Response?

Iros Author Response fits situations like: responding to IROS reviews given the traditional no-rebuttal model — pre-answering objections in the paper and video before submission; addressing the meta-review through camera-ready edits; writing RA-L response letters for the journal pathway; drafting reject-to-ICRA/CoRL/RA-L resubmission memos under double-anonymous rules.

How do I install Iros Author Response in Claude Code?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iros-author-response -a claude-code`. Or copy the skill folder (IROS-Skills/skills/iros-author-response in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/iros-author-response in your project. Claude Code loads it when a task matches its description.

How do I install Iros Author Response in Codex?

Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill iros-author-response -a codex`. Or copy the skill folder (IROS-Skills/skills/iros-author-response in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/iros-author-response in your project. Codex loads it when a task matches its description.

Can I use Iros Author Response 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 brycewang-stanford/Awesome-Journal-Skills --skill iros-author-response -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/iros-author-response, .gemini/skills/iros-author-response, .github/skills/iros-author-response and .opencode/skills/iros-author-response in your project.

What does Iros Author Response need to run?

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

Does Iros Author Response 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 Iros Author Response 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 Iros Author Response use?

Iros Author Response 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 Iros Author Response use?

About 953 tokens (SKILL.md is roughly 3.8k 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 Iros Author Response?

Skills that share tags, products or a category with Iros Author Response: Responsive Units (thedaviddias/Front-End-Checklist, 74k stars), Author Response Builder (aipoch/medical-research-skills, 1.9k stars), Rebuttal Response (M1n-n9/paper-lifecycle, 693 stars) and Hermes Agent Skill Authoring (NousResearch/hermes-agent, 252k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Iros Author Response?

brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,231 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.

Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.