Bio Workflows Chipseq Pipeline
GPTomics/bioSkills
Orchestrates the end-to-end ChIP-seq pipeline from FASTQ to blacklist-filtered, annotated peaks, chaining fastp QC, Bowtie2 alignment, pre-dedup library-complexity QC (NRF/PBC), duplicate removal…
Agent skill
Interspeech Reproducibility
by brycewang-stanford in brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER…
Install Interspeech Reproducibility
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill interspeech-reproducibility -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills interspeech-reproducibility --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/INTERSPEECH-Skills/skills/interspeech-reproducibility .claude/skills/interspeech-reproducibility && 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 "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .claude/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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/INTERSPEECH-Skills/skills/interspeech-reproducibilityType 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 interspeech-reproducibility -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills interspeech-reproducibility --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/INTERSPEECH-Skills/skills/interspeech-reproducibility .agents/skills/interspeech-reproducibility && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .agents/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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 interspeech-reproducibility -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills interspeech-reproducibility --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/INTERSPEECH-Skills/skills/interspeech-reproducibility .cursor/skills/interspeech-reproducibility && 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 "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .cursor/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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 INTERSPEECH-Skills/skills/interspeech-reproducibility--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 interspeech-reproducibility -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills interspeech-reproducibility --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/INTERSPEECH-Skills/skills/interspeech-reproducibility .gemini/skills/interspeech-reproducibility && 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 "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .gemini/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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 interspeech-reproducibilityInstalls 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 interspeech-reproducibility -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/INTERSPEECH-Skills/skills/interspeech-reproducibility .github/skills/interspeech-reproducibility && 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 "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .github/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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 interspeech-reproducibility -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 interspeech-reproducibility --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/INTERSPEECH-Skills/skills/interspeech-reproducibility .opencode/skills/interspeech-reproducibility && 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 "interspeech-reproducibility" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/INTERSPEECH-Skills/skills/interspeech-reproducibility into .opencode/skills/interspeech-reproducibility/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "interspeech-reproducibility", 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
interspeech-reproducibility- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 697 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER…
- Hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits
- SKILL.md covers The five decay channels, Corpus discipline, Objective metrics: publish the… and Subjective metrics: the…, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Publishing text-normalization and scoring rules that WER/EER silently depend on
What it does
Interspeech Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER silently depend on, documenting MOS listening-test protocols, reporting seeds and variance within 4 pages, and making toolkit recipes rerunnable.
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 Research & Science, covering Reproducible research and Database schema design. 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
- Hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits
- Publishing text-normalization and scoring rules that WER/EER silently depend on
- Documenting MOS listening-test protocols
- Reporting seeds and variance within 4 pages
Example prompts
- “/interspeech-reproducibility”
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
Interspeech Reproducibility loads about 1.6k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 697 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). 697 words, ~1,551 tokens.
Download SKILL.mdSave it as
.claude/skills/interspeech-reproducibility/SKILL.md (or your agent's skills folder).- name
- interspeech-reproducibility
- description
- Use when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER silently depend on, documenting MOS listening-test protocols, reporting seeds and variance within 4 pages, and making toolkit recipes rerunnable.
INTERSPEECH Reproducibility
Speech results decay through the measurement, not just the model. Two labs with identical checkpoints can report WERs a point apart because their text normalization differs, and two identical TTS systems can score half a MOS point apart under different listening panels. Interspeech reviewers know this, and the 4-page format means reproducibility is asserted through precise, compressed disclosure — there is no appendix to hide vagueness in.
The five decay channels
| Channel | How results drift | Pin it by |
|---|---|---|
| Corpus version & splits | "test" ≠ official test; filtered utterances | Name corpus version + official partition; list any filtering rule |
| Text normalization | casing, punctuation, numerals change WER | Publish the norm script; name the scorer (e.g., sclite/jiwer + config) |
| Trial lists / protocols | EER/minDCF move with the trial set | Cite the exact trial list file and calibration set |
| Subjective testing | MOS panels differ in raters, scale, stimuli | Report rater count, platform, instructions, #stimuli, CI |
| Training stochasticity | seed, data order, nondeterministic kernels | Seeds logged; ≥3 runs where feasible; mean ± sd |
Corpus discipline
- Name the release, not the family: "LibriSpeech test-other", "VoxCeleb1-O cleaned trial list", "CHiME-6 eval per the challenge rules" — each token is checkable.
- If you re-partition, justify it and publish the split manifests; private splits are the single most common irreproducibility at this venue.
- State licenses (see
interspeech-artifact-evaluation); a reader must know whether they can obtain your training data. - For multilingual claims, list the languages and hours per language — "50+ languages" without a table row per language is not reproducible.
Objective metrics: publish the ruler
WER is a Levenshtein distance over a normalization you chose. Reviewers who have been burned will ask:
- Which scoring tool and version, with which options?
- What text normalization (case, punctuation, number expansion, compound rules)?
- Insertion-penalty / LM-weight tuning: on which dev set?
- For EER/minDCF: which trial list, which prior/costs in the DCF?
- For enhancement: PESQ-WB or NB? STOI or ESTOI? Which reference alignment?
One sentence in the paper plus scripts in the repo answers all of it.
Subjective metrics: the protocol is the result
A MOS number without its protocol is decoration. The reportable minimum, fitted to about three lines of a 4-page paper:
Naturalness MOS: 5-point ACR; N=30 crowd raters (platform X), native speakers,
screened by anchor trials; 20 utterances/system, 8 systems, randomized;
95% CI via rater bootstrap. CMOS vs. baseline on the same panel.If a claim rests on ±0.1 MOS, it rests on nothing — pair MOS with CMOS or an objective proxy (e.g., a learned MOS predictor, clearly labeled as a proxy) and say whether the panel can resolve the difference.
Show full SKILL.md (308 more words)Show less
Variance and seeds inside 4 pages
- Prefer one honest line — "mean ± sd over 3 seeds; CI excludes the baseline" — over three extra ablations without variance.
- Bootstrap CIs at the utterance level for WER; matched-pairs significance (e.g., MAPSSWE-style or paired bootstrap) when claiming a system beats another.
- If compute allows only one run, say so and temper the claim's verbs accordingly.
Recipe rerunnability
Most Interspeech systems live in community toolkits (ESPnet, SpeechBrain, Kaldi, NeMo, k2, fairseq lineage). Reproducibility there means:
- Pin the toolkit commit and the recipe directory, not just the toolkit name.
- Diff-against-default: state which hyperparameters differ from the stock recipe — that diff is your method's footprint.
- Log the full config used for each table row; map rows to config files in the repo.
- Record hardware and wall-clock: "8×A100, 36h" tells readers whether they can replicate at all.
Review-time vs camera-ready disclosure
During double-blind review the repo must be anonymized or described-but-withheld; at camera-ready the links flip public. Write the reproducibility sentences so that only the URL changes, not the promises.
The disclosure block, worth three lines of the paper
A compact pattern that closes most reviewer doubts at once — adapt per task:
Setup: ESPnet2 (commit abc123), LibriSpeech 960h official splits;
Whisper-normalizer text rules; WER via jiwer 3.x, config in repo.
Training: 3 seeds (mean±sd reported), 8×A100, 30h/run; decoding:
beam 10, no external LM; dev-clean used for all tuning.Every clause preempts a specific review question; nothing in it costs a figure.
Reviewer questions to preempt
- "Is the gain inside seed noise?" → variance line present.
- "Which normalization produced these WERs?" → ruler named and shipped.
- "Did any tuning touch the test set?" → dev-only sentence present.
- "Can I obtain the training data?" → corpus + license named.
- "Would the MOS panel resolve this difference?" → CI + panel size reported.
If the paper answers all five before they are asked, the reproducibility paragraph has done its rhetorical job as well as its scientific one.
Output format
[Decay-channel audit] corpus / normalization / trials / subjective / seeds — pinned?
[Ruler published?] scoring tools + norm rules in repo: yes / partial / no
[Subjective protocol] complete per the reportable minimum? gaps
[Variance] runs, CI method, significance test used
[Recipe] toolkit+commit, config-per-row mapping, hardware line
[Weakest link] <the one channel most likely to break replication>Cross-check any cycle-specific checklist or disclosure field on the live CFP —
Interspeech has been adding evaluation-rigor language cycle by cycle (sources:
resources/official-source-map.md, checked 2026-07-08).
© 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 INTERSPEECH-Skills/skills/interspeech-reproducibility of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Interspeech Reproducibility 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 |
|---|---|---|---|---|---|---|
| Interspeech Reproducibility this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Bio Workflows Chipseq PipelineGPTomics/bioSkills | 1.2k | 1 repos | ~4k | Automated safety check: Pass | MIT | |
| Bio Differential Expression Edger BasicsGPTomics/bioSkills | 1.2k | 1 repos | ~5.5k | Automated safety check: Pass | MIT | |
| Bio Hi C Analysis Hic DifferentialGPTomics/bioSkills | 1.2k | 1 repos | ~5.5k | Automated safety check: Pass | MIT | |
| Peer ReviewK-Dense-AI/claude-scientific-writer | 2.4k | 2 repos | ~3.1k | Automated safety check: Notes | MIT | |
| CHARLS Paper Reproduction Guidexjtulyc/MedgeClaw | 617 | 1 repos | ~1.8k | Automated safety check: Pass | None |
Similar skills
Bio Differential Expression Edger Basics
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Performs differential expression on bulk RNA-seq count data with edgeR's negative-binomial GLM and quasi-likelihood F-test framework.
Bio Hi C Analysis Hic Differential
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Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries…
Peer Review
K-Dense-AI/claude-scientific-writer
Prepare evidence-bounded, constructive peer-review drafts and structured manuscript assessments.
CHARLS Paper Reproduction Guide
xjtulyc/MedgeClaw
Guides an agent through reproducing papers built on the CHARLS health and retirement survey, from variable mapping to cognition, depression and isolation scores.
Compute Environment Setup
aipoch/open-science
Prepares setup instructions and a named activation file for a user-managed software environment on an Open-Science SSH or Slurm compute host.
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Questions about Interspeech Reproducibility
What does Interspeech Reproducibility do?
A skill your agent uses when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER…. Interspeech Reproducibility is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits, publishing text-normalization and scoring rules that WER/EER silently depend on, documenting MOS listening-test protocols, reporting seeds and variance within 4 pages, and making toolkit recipes rerunnable.
When should I use Interspeech Reproducibility?
Interspeech Reproducibility fits situations like: hardening the reproducibility of an INTERSPEECH paper — pinning corpus versions and official splits; publishing text-normalization and scoring rules that WER/EER silently depend on; documenting MOS listening-test protocols; reporting seeds and variance within 4 pages.
How do I install Interspeech Reproducibility in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill interspeech-reproducibility -a claude-code`. Or copy the skill folder (INTERSPEECH-Skills/skills/interspeech-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/interspeech-reproducibility in your project. Claude Code loads it when a task matches its description.
How do I install Interspeech Reproducibility in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill interspeech-reproducibility -a codex`. Or copy the skill folder (INTERSPEECH-Skills/skills/interspeech-reproducibility in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/interspeech-reproducibility in your project. Codex loads it when a task matches its description.
Can I use Interspeech Reproducibility 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 interspeech-reproducibility -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/interspeech-reproducibility, .gemini/skills/interspeech-reproducibility, .github/skills/interspeech-reproducibility and .opencode/skills/interspeech-reproducibility in your project.
What does Interspeech Reproducibility need to run?
SKILL.md names no scripts, command-line tools or credentials: Interspeech Reproducibility is instructions for the agent only.
Does Interspeech Reproducibility 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 Interspeech Reproducibility 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 Interspeech Reproducibility use?
Interspeech Reproducibility 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 Interspeech Reproducibility 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 Interspeech Reproducibility?
Skills that share tags, products or a category with Interspeech Reproducibility: Bio Workflows Chipseq Pipeline (GPTomics/bioSkills, 1.2k stars), Bio Differential Expression Edger Basics (GPTomics/bioSkills, 1.2k stars), Bio Hi C Analysis Hic Differential (GPTomics/bioSkills, 1.2k stars) and Peer Review (K-Dense-AI/claude-scientific-writer, 2.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Interspeech Reproducibility?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,228 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.