A skill your agent uses when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis…

MITAuto-check passed

Install Issta Topic Selection

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

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

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

At a glance

A skill your agent uses when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis…

  • Deciding whether a project is a strong ISSTA fit versus ICSE
  • SKILL.md covers Fit test, Fit signal table, Vignette: where a repair… and Sharpening moves before…, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Identifying whether the contribution is a testing/analysis technique

What it does

Issta Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis technique, characterizing its evaluation shape, and sharpening the framing before writing begins.

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.

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

  • Deciding whether a project is a strong ISSTA fit versus ICSE
  • Identifying whether the contribution is a testing/analysis technique
  • Characterizing its evaluation shape
  • Sharpening the framing before writing begins

Example prompts

  • “/issta-topic-selection”

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 Topic Selection loads about 1.1k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 500 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~73
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). 500 words, ~1,106 tokens.

Download SKILL.mdSave it as .claude/skills/issta-topic-selection/SKILL.md (or your agent's skills folder).
name
issta-topic-selection
description
Use when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis technique, characterizing its evaluation shape, and sharpening the framing before writing begins.

ISSTA Topic Selection

Use this before writing. ISSTA is the venue for techniques that test or analyze software — that find, characterize, or reason about program behaviour and defects — evaluated on real subjects. The routing decision is mostly about whether that is the core of the contribution, or an ingredient in something broader.

Fit test

  • Prefer ISSTA when the contribution is a testing or analysis technique: test generation, fuzzing, symbolic or concolic execution, static/dynamic analysis, fault localization, program-repair evaluation, sanitizers, or an empirical study about testing and analysis.
  • Route to ICSE or FSE when the contribution is broader software engineering: requirements, design, process, developer studies, or a technique whose testing angle is secondary. These are the general SE flagships; ISSTA is the testing/analysis specialist.
  • Route to ASE when the core is automation of an SE task and the testing/analysis content is a means rather than the end.
  • Route to ICST when the work is testing-focused but a better fit for a testing-specific audience, or is more applied/industrial than ISSTA's research-track bar.
  • Route to PLDI, POPL, or CAV/TACAS when the contribution is primarily a language/analysis foundation or a verification result, and the empirical bug-finding evaluation is secondary.
  • Route to an SE journal (TSE, TOSEM, EMSE) when the work needs journal-length exposition or is an extended empirical study beyond a conference's scope.

Fit signal table

Signal in the projectISSTA reading
A technique that finds bugs / analyzes behaviour, evaluated on real subjectsCore fit — the house genre
A shared benchmark or testing infrastructure others will reuseCore fit (see Defects4J lineage)
A rigorous empirical study of a testing/analysis technique classCore fit — evaluation is a contribution
A broad SE process, requirements, or human-factors resultBetter at ICSE or FSE
A formal analysis/verification result with a thin empirical sideBetter at PLDI/POPL or CAV
A tool-automation contribution where testing is incidentalBetter at ASE
Show full SKILL.md (190 more words)Show less

Vignette: where a repair project goes

A project produces an automated program-repair technique with a new patch-ranking method and an evaluation on Defects4J. ISSTA reading: strong fit — a testing/analysis technique with a real benchmark and a bug-finding-adjacent evaluation. Reframe it as a study of why existing repair tools produce incorrect patches and it is still ISSTA (an evaluation contribution). Turn it into a formal soundness result about the repair calculus with little empirical evaluation, and PLDI or CAV becomes the better home; grow it into a broad process for integrating repair into developer workflows, and ICSE fits better.

Sharpening moves before committing

  • Name the technique and the property it targets. If the core is not a testing/analysis technique or a study of one, the ISSTA framing does not exist.
  • Confirm an established benchmark exists or can be built; an evaluation a reviewer cannot compare to prior work is a quiet fit failure here.
  • Check the evaluation can be run at a fair, equal budget against the nearest tool — ISSTA's comparison bar is high.
  • Topic emphasis drifts between editions; scan the current call's topics of interest before final routing.
text
Is the core a technique that tests or analyzes software,
evaluated on real subjects against a fair baseline?
  yes -> ISSTA is a strong candidate
  broader SE / process / human factors -> ICSE / FSE
  automation-first -> ASE ; testing-applied -> ICST
  formal / verification-first -> PLDI / POPL / CAV

Output format

text
[Fit] strong ISSTA / possible ISSTA / better elsewhere
[Best venue] ISSTA / ICSE / FSE / ASE / ICST / PLDI / CAV / journal
[Contribution sentence] <one sentence naming technique + property>
[Top rejection risk] <originality / evaluation / comparison / scope>
[Next action] <technique work, benchmark choice, framing, or venue switch>

© 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-topic-selection of brycewang-stanford/Awesome-Journal-Skills.

Open the folder on GitHubat commit 932eb23

Compare with similar skills

Issta Topic Selection 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 Topic Selection compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Issta Topic Selection this skillbrycewang-stanford/Awesome-Journal-Skills1.2k—~1.1kAutomated safety check: PassMIT
Table Fitasgeirtj/system_prompts_leaks69k—~772Automated safety check: PassCC0-1.0
Furniture Fit Checkpascalorg/editor25k—~5.1kAutomated safety check: PassMIT
TopicsZimoLiao/scholaraio577—~294Automated safety check: PassMIT
Topic Modelingbrycewang-stanford/Auto-Empirical-Research-Skills4.6k—~3.7kAutomated safety check: PassCustom licence
Bestblogs Topicginobefun/BestBlogs4.1k—~670Automated safety check: PassNone

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Questions about Issta Topic Selection

What does Issta Topic Selection do?

A skill your agent uses when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis…. Issta Topic Selection is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when deciding whether a project is a strong ISSTA fit versus ICSE, FSE, ASE, ICST, PLDI/CAV, or an SE journal, identifying whether the contribution is a testing/analysis technique, characterizing its evaluation shape, and sharpening the framing before writing begins.

When should I use Issta Topic Selection?

Issta Topic Selection fits situations like: deciding whether a project is a strong ISSTA fit versus ICSE; identifying whether the contribution is a testing/analysis technique; characterizing its evaluation shape; sharpening the framing before writing begins.

How do I install Issta Topic Selection in Claude Code?

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

How do I install Issta Topic Selection in Codex?

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

Can I use Issta Topic Selection 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-topic-selection -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-topic-selection, .gemini/skills/issta-topic-selection, .github/skills/issta-topic-selection and .opencode/skills/issta-topic-selection in your project.

What does Issta Topic Selection need to run?

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

Does Issta Topic Selection 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 Topic Selection 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 Topic Selection use?

Issta Topic Selection 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 Topic Selection use?

About 1.1k tokens (SKILL.md is roughly 4.4k 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 Topic Selection?

Skills that share tags, products or a category with Issta Topic Selection: Table Fit (asgeirtj/system_prompts_leaks, 69k stars), Furniture Fit Check (pascalorg/editor, 25k stars), Topics (ZimoLiao/scholaraio, 577 stars) and Topic Modeling (brycewang-stanford/Auto-Empirical-Research-Skills, 4.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Issta Topic Selection?

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.