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A skill your agent uses when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard…
Install Icsme Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experiments --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .claude/skills/icsme-experiments && rm -rf skills-srcUse ~/.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/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .claude/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experimentsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experiments --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .agents/skills/icsme-experiments && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .agents/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experiments --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .cursor/skills/icsme-experiments && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .cursor/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path ICSME-Skills/skills/icsme-experiments--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experiments --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .gemini/skills/icsme-experiments && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .gemini/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experimentsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .github/skills/icsme-experiments && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .github/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills icsme-experiments --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/ICSME-Skills/skills/icsme-experiments .opencode/skills/icsme-experiments && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "icsme-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/ICSME-Skills/skills/icsme-experiments into .opencode/skills/icsme-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "icsme-experiments", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
icsme-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 554 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard…
- Auditing IEEE ICSME empirical evaluations
- SKILL.md covers Evaluation audit, Claim-to-evidence design table, Provenance floor for mining… and Contamination-aware LLM…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Covering real evolving subject systems
What it does
Icsme Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard statistics and effect sizes, change-history and survivorship confounds, qualitative rigor, contamination-aware LLM ablations, and matching evidence to the shape of each maintenance/evolution claim.
Its SKILL.md is about 1.6k 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 Data & Analytics, covering Statistics. 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
- Auditing IEEE ICSME empirical evaluations
- Covering real evolving subject systems
- Mining-software-repositories provenance
- SE-standard statistics and effect sizes
Example prompts
- “/icsme-experiments”
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
Icsme Experiments loads about 1.6k tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 554 words of instructions outside code blocks.
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). 554 words, ~1,554 tokens.
Download SKILL.mdSave it as
.claude/skills/icsme-experiments/SKILL.md (or your agent's skills folder).- name
- icsme-experiments
- description
- Use when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard statistics and effect sizes, change-history and survivorship confounds, qualitative rigor, contamination-aware LLM ablations, and matching evidence to the shape of each maintenance/evolution claim.
ICSME Experiments
Use this before submission when the empirical story is not yet locked. ICSME reviewers are maintenance and evolution empiricists, and because the venue has no revision round, the evaluation must be complete on submission — you cannot promise a missing analysis and add it later. The organizing principle is evidence proportional to the claim, tested on real systems with real change history, not on synthetic snapshots.
Evaluation audit
- Match evidence to the claim shape. A claim about maintenance effort needs effort or proxy data defended as a proxy; a claim about change impact needs real change sets; a claim about comprehension needs a human study; a claim about debt needs a debt measurement, not lines of code. Accuracy against a convenient label is not evidence for a maintenance-practice claim.
- Use real, evolving subject systems, sampled by a stated criterion over a stated time window, and list them in the artifact. A single snapshot cannot support an evolution claim.
- Pin mining provenance (see the code block): repository SHAs, extraction dates, inclusion/ exclusion criteria, and fork/duplicate/bot handling. Silent inclusion of forks or bot commits skews every downstream evolution number.
- Choose fair baselines, including the strongest prior maintenance technique and a simple-but-reasonable alternative, tuned with a documented, equal budget. An untuned baseline is a scored weakness a rebuttal cannot fully repair.
- Report SE-standard statistics: effect sizes (not just p-values), confidence intervals, appropriate tests, and corrections for multiple comparisons; say how many runs and what variance.
- Handle change-history confounds by design: survivorship (systems that died mid-history), releases vs. commits as the unit of evolution, and time-window sensitivity.
- Hold qualitative work to method: coding schemes, inter-rater agreement, saturation, and an audit trail — mixed-methods maintenance studies are native to ICSME.
Show full SKILL.md (269 more words)Show less
Claim-to-evidence design table
| Maintenance/evolution claim | Matching evidence | Reject pattern avoided |
|---|---|---|
| "Technique reduces change impact" | Real change sets from history, set-size deltas with CIs vs. tuned baseline | "Evaluated on synthetic edits only" |
| "Refactoring preserves behaviour" | Test outcomes / regression evidence across applications on real code | "Assumed safe, never checked" |
| "Debt predicts future defects" | Longitudinal link from debt measure to later real defects, with survivorship handled | "Cross-sectional correlation claimed causal" |
| "Improves comprehension" | Human study with tasks, accuracy/time, effect sizes | "Tool complexity mistaken for understanding" |
| "Finding holds across systems" | Diverse, dated sample + explicit external-validity limits | "One ecosystem, claimed universal" |
| "The model adds the value" | Ablation removing the model vs. lexical/heuristic features | "Model's marginal contribution never isolated" |
Provenance floor for mining studies (the ICSME core)
[Corpus] pin repository SHAs; record extraction date and the time window studied;
archive the *extracted* dataset, not just the query
[Selection] state inclusion/exclusion criteria and resulting N; ship the filtering script
[Hygiene] document fork/duplicate/bot handling; report how merges and renames were resolved
[Unit] state whether the unit is commit, PR, release, or file, and defend it for the claim
[History] address survivorship and left-truncation of the change history explicitlyContamination-aware LLM evaluation
When an LLM is in the loop (increasingly common for comprehension, summarization, and repair):
[Contamination] are subject systems plausibly in the model's training data? report model cutoff
vs. project/commit dates; prefer post-cutoff or held-out systems
[Determinism] fix temperature/seed where possible; report the sampling settings
[Caching] store raw prompts and raw responses in the artifact; a live-API study re-samples
rather than reproduces
[Versioning] record exact model identifiers and access dates; models drift under a name
[Ablation] isolate the model's marginal value against a non-LLM maintenance baselineVignette: evaluating a change-impact technique
Suppose the paper claims a technique predicts change-impact sets more precisely than a prior tool. The matching plan: draw real change sets from dated release histories of several evolving systems; run both tools with an equal, documented budget; report precision/recall with confidence intervals and an effect size; manually inspect a sample of predicted impacts for spurious inclusion; handle survivorship by stating which systems' histories are truncated; and bound external validity (languages, domains) as a threat — every number traceable to a logged run in the artifact.
Statistical reporting floor
- Effect sizes and confidence intervals for every quantitative comparison; say what the intervals represent.
- Number of runs and the source of variance for any stochastic component.
- The compute and mining time actually consumed, not vague feasibility language.
Output format
[Evaluation readiness] strong / adequate / weak
[Claim -> evidence map] <claim: systems/history-window/metric/statistic>
[Mining provenance] <SHAs / extraction date / selection / fork-bot hygiene handled? yes/no>
[Baseline fairness] <baseline -> tuned? equal budget? documented?>
[Confounds by design] <survivorship / unit-of-analysis / contamination -> how bounded>
[Decision-critical gap] <the one thing that must be complete before submission — no revision round>© 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 ICSME-Skills/skills/icsme-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Icsme Experiments 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Icsme Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.8k | 4 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.6k | 16 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| Statistical Powerspacering-net/codeg | 3.8k | 2 repos | ~3.6k | Automated safety check: Notes | MIT | |
| AI Daily DigestvigorX777/ai-daily-digest | 1.6k | — | ~1.3k | Automated safety check: Pass | None |
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Questions about Icsme Experiments
What does Icsme Experiments do?
A skill your agent uses when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard…. Icsme Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing IEEE ICSME empirical evaluations, covering real evolving subject systems, mining-software-repositories provenance, fair baselines, SE-standard statistics and effect sizes, change-history and survivorship confounds, qualitative rigor, contamination-aware LLM ablations, and matching evidence to the shape of each maintenance/evolution claim.
When should I use Icsme Experiments?
Icsme Experiments fits situations like: auditing IEEE ICSME empirical evaluations; covering real evolving subject systems; mining-software-repositories provenance; SE-standard statistics and effect sizes.
How do I install Icsme Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a claude-code`. Or copy the skill folder (ICSME-Skills/skills/icsme-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/icsme-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Icsme Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icsme-experiments -a codex`. Or copy the skill folder (ICSME-Skills/skills/icsme-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/icsme-experiments in your project. Codex loads it when a task matches its description.
Can I use Icsme Experiments 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 icsme-experiments -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/icsme-experiments, .gemini/skills/icsme-experiments, .github/skills/icsme-experiments and .opencode/skills/icsme-experiments in your project.
What does Icsme Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Icsme Experiments is instructions for the agent only.
Does Icsme Experiments 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 Icsme Experiments 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 Icsme Experiments use?
Icsme Experiments 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 Icsme Experiments use?
About 1.6k tokens (SKILL.md is roughly 6.2k 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 Icsme Experiments?
Skills that share tags, products or a category with Icsme Experiments: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.8k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.6k stars) and Statistical Power (spacering-net/codeg, 3.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Icsme Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 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.