A skill your agent uses when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the…

MITAuto-check passedResearch & Science

Install Issta Review Process

skills CLI
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill issta-review-process -a claude-code

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

GitHub CLI
$ gh skill install brycewang-stanford/Awesome-Journal-Skills issta-review-process --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/ISSTA-Skills/skills/issta-review-process .claude/skills/issta-review-process && 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
issta-review-process
GitHub stars
1.2k
Token cost
~1.1k tokens
SKILL.md length
478 words
Files
1
Skills in repo
2,387
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the…

  • Planning around ISSTA peer review
  • SKILL.md covers Process model, The named evaluation criteria, Who reviews here and Stage-by-stage realism, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Covering double-anonymous reviewing

What it does

Issta Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the phase-two major-revision resubmission, the named evaluation criteria, how the decision is actually synthesized, and how earlier editions ran multiple rolling deadlines.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Peer review. 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

  • Planning around ISSTA peer review
  • Covering double-anonymous reviewing
  • At least three PC reviews
  • The Accept/Major-Revision/Reject outcome model

Example prompts

  • “/issta-review-process”

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

Issta Review Process loads about 1.1k tokens when it runs. Until then it costs about 91 tokens; SKILL.md has 478 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
~1.1k

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). 478 words, ~1,066 tokens.

Download SKILL.mdSave it as .claude/skills/issta-review-process/SKILL.md (or your agent's skills folder).
name
issta-review-process
description
Use when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the phase-two major-revision resubmission, the named evaluation criteria, how the decision is actually synthesized, and how earlier editions ran multiple rolling deadlines.

ISSTA Review Process

Use this to reason about review-stage strategy. ISSTA review is double-anonymous and its outcome model is richer than accept/reject, so plan around the Major-Revision path from the start. Reopen the current call and dates page before making process claims — the number of deadlines and the exact mechanics change between editions.

Process model

  • Reviewing is double-anonymous: reviewers do not see author identities and authors do not see reviewer identities.
  • Each paper receives at least three PC reviews; chairs solicit more when expertise is thin or reviewers disagree sharply.
  • First-round outcomes are Accept, Major Revision, or Reject. A Major-Revision paper revises against a fixed later deadline and receives a terminal decision — it is a real second chance, not a soft reject, and reviewers expect the revision to address their points concretely.
  • Earlier editions (e.g. ISSTA 2023, 2024) ran two rolling submission deadlines, where a first-deadline paper could be sent a major revision to the second deadline while second-deadline papers got only accept/reject. The multi-round model is genuine ISSTA history; its exact shape is cycle-specific, so confirm the current one.
  • Accepted papers are published in the ACM Digital Library, so final metadata and camera-ready compliance matter alongside the initial decision.

The named evaluation criteria

CriterionWhat raises itWhat sinks it
OriginalityA technique or question the field did not haveA re-parameterized variant of existing work
Importance of contributionA result the testing/analysis community will reuseA narrow gain with no reuse story
SoundnessClaims scoped to what is actually shownOverclaimed scope; unstated assumptions
EvaluationReal subjects, fair baselines, proper statisticsToy subjects, mis-configured baselines, single runs
PresentationA clear threat model and evaluation contractUndefined scope; results without protocol
Comparison to related workDelta stated against the nearest techniquesMissing the closest competitor
Verifiability / transparencyPinned subjects and a runnable artifactUnshared subjects, unregenerable tables

The last two — comparison and verifiability — are where testing/analysis papers most often lose avoidable ground, because the nearest baseline and the shared artifact are both checkable.

Show full SKILL.md (144 more words)Show less

Who reviews here

  • The PC is specialized in testing and analysis, so a reviewer will know the closest tool, the standard benchmark, and the usual statistical protocol. Vague baselines and hand-picked subjects get caught rather than skimmed past.
  • Borderline papers usually fall on one of three edges: an evaluation that does not use an established benchmark, a baseline configured to lose, or a claim broader than the subjects tested.

Stage-by-stage realism

  • Initial reviews: read for the criteria the meta-reviewer will weigh, not for reviewer tone.
  • Response / discussion: address the decision-critical objection first; an early precise reply beats a late comprehensive one.
  • Major Revision: treat every comment as a tracked change and walk the ledger in the resubmission; reviewers who see their points addressed in order revise upward.
  • Decision: the meta-review synthesizes; one unresolved soundness or evaluation objection outweighs several resolved presentation complaints.

Output format

text
[Current stage] submitted / reviews / response / major-revision / decision / camera-ready
[Outcome model] accept / major-revision / reject
[Decision actors] <reviewers / meta-reviewer / chairs>
[Likely leverage] <soundness / evaluation / comparison / verifiability>
[Forbidden moves] <identity leak / unpromised new results in the box>
[Next response move] <one action>

© 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 ISSTA-Skills/skills/issta-review-process of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Issta Review Process 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.

Issta Review Process compared with similar skills
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Scholar Evaluationspacering-net/codeg3.9k11 repos~3.2kAutomated safety check: PassMIT
Academic Paper Writing PipelineImbad0202/academic-research-skills51k—~16kAutomated safety check: PassCustom licence
Academic Paper ReviewerImbad0202/academic-research-skills51k—~11kAutomated safety check: PassCustom licence
Peer ReviewK-Dense-AI/claude-scientific-writer2.4k2 repos~3.1kAutomated safety check: NotesMIT

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Questions about Issta Review Process

What does Issta Review Process do?

A skill your agent uses when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the…. Issta Review Process is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when explaining or planning around ISSTA peer review, covering double-anonymous reviewing, at least three PC reviews, the Accept/Major-Revision/Reject outcome model, the phase-two major-revision resubmission, the named evaluation criteria, how the decision is actually synthesized, and how earlier editions ran multiple rolling deadlines.

When should I use Issta Review Process?

Issta Review Process fits situations like: planning around ISSTA peer review; covering double-anonymous reviewing; at least three PC reviews; the Accept/Major-Revision/Reject outcome model.

How do I install Issta Review Process in Claude Code?

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

How do I install Issta Review Process in Codex?

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

Can I use Issta Review Process 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 issta-review-process -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/issta-review-process, .gemini/skills/issta-review-process, .github/skills/issta-review-process and .opencode/skills/issta-review-process in your project.

What does Issta Review Process need to run?

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

Does Issta Review Process 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 Issta Review Process 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 Issta Review Process use?

Issta Review Process 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 Issta Review Process use?

About 1.1k tokens (SKILL.md is roughly 4.3k 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 Issta Review Process?

Skills that share tags, products or a category with Issta Review Process: Peer Review (spacering-net/codeg, 3.9k stars), Scholar Evaluation (spacering-net/codeg, 3.9k stars), Academic Paper Writing Pipeline (Imbad0202/academic-research-skills, 51k stars) and Academic Paper Reviewer (Imbad0202/academic-research-skills, 51k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Issta Review Process?

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.