Social
coreyhaines31/marketingskills
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, or Facebook, or wants to do social listening and engagement triage.
A skill your agent uses when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort…
Install Popl Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popl-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popl-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/POPL-Skills/skills/popl-experiments .claude/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .claude/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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/POPL-Skills/skills/popl-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 popl-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popl-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/POPL-Skills/skills/popl-experiments .agents/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .agents/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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 popl-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popl-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/POPL-Skills/skills/popl-experiments .cursor/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .cursor/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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 POPL-Skills/skills/popl-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 popl-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popl-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/POPL-Skills/skills/popl-experiments .gemini/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .gemini/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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 popl-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 popl-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/POPL-Skills/skills/popl-experiments .github/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .github/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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 popl-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 popl-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/POPL-Skills/skills/popl-experiments .opencode/skills/popl-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 "popl-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/POPL-Skills/skills/popl-experiments into .opencode/skills/popl-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popl-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
popl-experiments- GitHub stars
- 1.2k
- Token cost
- ~892 tokens
- SKILL.md length
- 356 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort…
- Designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization
- SKILL.md covers Match evidence to claim, Proof effort is data at this…, Case-study discipline and Performance numbers, when…, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Reporting proof effort and case-study coverage honestly
What it does
Popl Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort and case-study coverage honestly; and keeping performance numbers in a supporting role so the formal claim stays the paper's center of gravity.
Its SKILL.md is about 890 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 Writing & Content. 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
- Designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization
- Reporting proof effort and case-study coverage honestly
- Keeping performance numbers in a supporting role so the formal claim stays the papers center of gravity
Example prompts
- “/popl-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 (its code samples are bash).
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
Popl Experiments loads about 892 tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 356 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). 356 words, ~892 tokens.
Download SKILL.mdSave it as
.claude/skills/popl-experiments/SKILL.md (or your agent's skills folder).- name
- popl-experiments
- description
- Use when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort and case-study coverage honestly; and keeping performance numbers in a supporting role so the formal claim stays the paper's center of gravity.
POPL Experiments and Empirical Evidence
POPL welcomes experimental papers, but the evaluation's job differs from a systems
venue: at POPL, evidence demonstrates that the formal idea is realizable and
relevant, it does not substitute for the theorem. Calibrate the empirical section
to the claim it supports, and no further. (Venue facts referenced here were checked
2026-07-08; see resources/official-source-map.md.)
Match evidence to claim
| Claim in the paper | Right evidence | Wrong evidence |
|---|---|---|
| "The type system is sound" | Proof (mechanized or on-paper, popl-reproducibility) | A test suite that found no counterexample |
| "The analysis is precise enough to be useful" | Case studies on real programs with found/missed counts | One toy example |
| "The logic scales to real proofs" | Proof effort data: LOC, person-time, lemma reuse across case studies | Adjectives ("lightweight," "practical") |
| "Checking is fast enough for interaction" | Timings on stated hardware with input sizes | Asymptotic claims dressed as measurements |
| "The translation preserves behavior" | The theorem, plus differential testing as a sanity layer | Testing alone |
Proof effort is data at this venue
Papers about logics, tactics, and frameworks make usability claims; the honest currency is effort accounting. Report it like a measurement, mechanically:
# Rocq/Coq development: spec vs proof line counts per file
coqwc theories/*.v | tail -5
# Lean 4: declaration counts as a proxy for library size
grep -rcE '^(theorem|lemma|def) ' Src/ | sort -t: -k2 -nr | head
# Case-study table skeleton: program, LOC, proved property, person-days, reused lemmasState what the numbers do not show: person-days depend on author expertise, and line counts are assistant-specific. An honest caveat paragraph here reads as maturity, not weakness.
Show full SKILL.md (143 more words)Show less
Case-study discipline
- Choose case studies that stress different features of the formalism, and say which feature each exercises; three variations on one pattern count as one.
- Report failures and near-misses: the program the analysis could not verify, the proof that needed a manual bridge lemma. POPL reviewers trust evaluations that contain bad news.
- Distinguish the artifact language from the ambient claim: results for a core calculus fragment must not be narrated as results for the full language.
- If a baseline tool exists, compare capability first (what each can express or verify) and performance second.
Performance numbers, when present
Keep them survivable rather than spectacular: fixed machine spec, versioned inputs,
repeated runs with dispersion, scripts in the artifact so evaluators can regenerate
every table (popl-artifact-evaluation). A slow but sound prototype is publishable
at POPL; an irreproducible speedup claim is a liability everywhere.
Output format
[Claim-evidence map] <each empirical claim -> its evidence type; mismatches flagged>
[Effort accounting] <LOC/person-time/case-study table present? caveats stated?>
[Bad-news audit] <failures and limitations reported, or missing>
[Regenerability] <scripts + machine spec + versions for every number>© 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 POPL-Skills/skills/popl-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Popl 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 |
|---|---|---|---|---|---|---|
| Popl Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~892 | Automated safety check: Pass | MIT | |
| Socialcoreyhaines31/marketingskills | 54k | 4 repos | ~4.5k | Automated safety check: Pass | MIT | |
| HumanizerAzure-Samples/interview-coach-agent-framework | 172 | 37 repos | ~5.8k | Automated safety check: Pass | MIT | |
| Avoid AI Writingconorbronsdon/avoid-ai-writing | 4.9k | 3 repos | ~8.1k | Automated safety check: Pass | MIT | |
| JavaScript Concept Fact Checkerleonardomso/33-js-concepts | 67k | 1 repos | ~5k | Automated safety check: Pass | MIT | |
| User-Facing Text Cleanupguillaumemeyer/watermarks-remover | 24k | — | ~3.5k | Automated safety check: Pass | MIT |
Similar skills
- Official
Humanizer
Azure-Samples/interview-coach-agent-framework
Remove signs of AI-generated writing from text. An agent skill from Azure-Samples/interview-coach-agent-framework.
Avoid AI Writing
conorbronsdon/avoid-ai-writing
Audit and rewrite content to remove AI writing patterns ("AI-isms").
JavaScript Concept Fact Checker
leonardomso/33-js-concepts
Verifies the technical accuracy of JavaScript concept pages by checking code examples, MDN and ECMAScript claims and external links through a five-phase method.
User-Facing Text Cleanup
guillaumemeyer/watermarks-remover
Audits prose for invisible Unicode characters and rewrites it while keeping facts, citations, code and required disclosures unchanged and the writer's voice intact.
Install Anti Slop
trycompai/crm
Install and configure the anti-slop Oxlint plugin in a local TypeScript or JavaScript repository.
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Categories
Questions about Popl Experiments
What does Popl Experiments do?
A skill your agent uses when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort…. Popl Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization, a prototype, case studies, or benchmarks; reporting proof effort and case-study coverage honestly; and keeping performance numbers in a supporting role so the formal claim stays the paper's center of gravity.
When should I use Popl Experiments?
Popl Experiments fits situations like: designing the empirical component of a POPL paper — deciding whether evidence should be a mechanization; reporting proof effort and case-study coverage honestly; keeping performance numbers in a supporting role so the formal claim stays the papers center of gravity.
How do I install Popl Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popl-experiments -a claude-code`. Or copy the skill folder (POPL-Skills/skills/popl-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/popl-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Popl Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popl-experiments -a codex`. Or copy the skill folder (POPL-Skills/skills/popl-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/popl-experiments in your project. Codex loads it when a task matches its description.
Can I use Popl 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 popl-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/popl-experiments, .gemini/skills/popl-experiments, .github/skills/popl-experiments and .opencode/skills/popl-experiments in your project.
What does Popl Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Popl Experiments is instructions for the agent only.
Does Popl 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 Popl 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 Popl Experiments use?
Popl 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 Popl Experiments use?
About 892 tokens (SKILL.md is roughly 3.6k 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 Popl Experiments?
Skills that share tags, products or a category with Popl Experiments: Social (coreyhaines31/marketingskills, 54k stars), Humanizer (Azure-Samples/interview-coach-agent-framework, 172 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars) and JavaScript Concept Fact Checker (leonardomso/33-js-concepts, 67k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Popl Experiments?
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.