A skill your agent uses when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill podc-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills podc-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/PODC-Skills/skills/podc-experiments .claude/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .claude/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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/PODC-Skills/skills/podc-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 podc-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills podc-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/PODC-Skills/skills/podc-experiments .agents/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .agents/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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 podc-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills podc-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/PODC-Skills/skills/podc-experiments .cursor/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .cursor/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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 PODC-Skills/skills/podc-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 podc-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills podc-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/PODC-Skills/skills/podc-experiments .gemini/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .gemini/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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 podc-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 podc-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/PODC-Skills/skills/podc-experiments .github/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .github/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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 podc-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 podc-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/PODC-Skills/skills/podc-experiments .opencode/skills/podc-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 "podc-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/PODC-Skills/skills/podc-experiments into .opencode/skills/podc-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "podc-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.
podc-experimentsA skill your agent uses when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark.
Podc Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark. Covers matching upper and lower bounds, tightness arguments, model and assumption stress-tests, adversary-strength calibration, and the honest, clearly-optional role of any simulation in a distributed-computing-theory paper.
Its SKILL.md is about 1.5k 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 Testing & QA, covering Load testing and Performance reviews. 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.
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
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.
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.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Podc Experiments loads about 1.5k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 582 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.
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.
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 582 words, ~1,454 tokens.
.claude/skills/podc-experiments/SKILL.md (or your agent's skills folder).At PODC the "experiment" is a proof, and the strongest result is a matching bound. This skill is the theory analogue of an empirical-evaluation section: it is about making the evidence for correctness and optimality as strong as the venue expects. There is no benchmark leaderboard, no artifact track, and a simulation never establishes the result — it can only illustrate it.
| Claim | What counts as evidence at PODC | Common failure caught |
|---|---|---|
| "Algorithm A solves problem P in model M" | A proof of the required properties (e.g., agreement, validity, termination) in exactly M | Property proved in a stronger model than claimed |
| "A costs O(f(n))" | A proof of the upper bound over all executions/adversary choices | Bound holds only in the best case, not worst/expected as stated |
| "A is optimal" | A matching Ω(f(n)) lower bound in the same model | "Optimal" asserted with no lower bound |
| "P is impossible in M" | An impossibility proof (valency, indistinguishability, covering) | Impossibility shown for a weaker model than claimed |
| "A self-stabilizes" | A proof of convergence from every state + closure | Convergence shown from some states only |
A PODC upper bound is good; an upper bound plus a matching lower bound is the venue's gold standard, because together they close the problem. Before submission, ask:
The most common fatal flaw at PODC is a proof that quietly relies on an assumption stronger than the stated model. Audit every assumption:
[Timing] does any step assume a message arrives "soon" in an asynchronous model? (illegal)
[Faults] does the proof assume a Byzantine party behaves in a bounded way? (only if justified)
[Adversary] is the adversary adaptive as claimed, or does the analysis secretly need oblivious?
[Atomicity] in shared memory, are the assumed primitives (CAS, LL/SC, registers) really available?
[Randomness] does correctness need a shared coin the model does not provide?
[Initialization] for self-stabilization, does convergence hold from *every* configuration?For each, either the proof survives the weakest form of the assumption in your model box, or the theorem statement must be weakened to name the stronger assumption. This audit is the theory equivalent of a threats-to-validity section, and reviewers perform it whether or not you do.
If your paper includes a simulation (many PODC papers include none), it must be framed as optional:
podc-topic-selection).podc-reproducibility and podc-submission).[ ] Every claimed property is proved in exactly the stated model (no assumption creep)
[ ] Upper bounds hold in the stated case (worst/expected), not just best case
[ ] Optimality claims carry a matching lower bound (or are downgraded to "we conjecture / leave open")
[ ] Resilience threshold stated and, if claimed optimal, backed by an impossibility
[ ] Adversary strength and randomness assumptions match the proof's real needs
[ ] Any simulation is labeled optional, with ranges/trials/seeds, and establishes nothing[Claim -> evidence] each theorem mapped to its proof; property proved in the stated model?
[Tightness] matching lower bound present / cited / proved / honestly left open?
[Assumption audit] timing/faults/adversary/atomicity/randomness/initialization all consistent with the model box?
[Adversary/regime] strength and parameter range stated correctly?
[Simulation] absent / present-and-labeled-optional (ranges, trials, seeds)?
[Fix queue] <assumption creep to fix; missing lower bound; overclaimed optimality>© 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
Just SKILL.md in PODC-Skills/skills/podc-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Podc 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 |
|---|---|---|---|---|---|---|
| Podc Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Neurips Experimentsfranklee16/academic-research-skills | 223 | 1 repos | ~465 | Automated safety check: Pass | None | |
| Thinking Partnermattnowdev/thinking-partner | 206 | — | ~4.4k | Automated safety check: Pass | MIT | |
| Risk AnalyzerCoWork-OS/CoWork-OS | 473 | — | ~779 | Automated safety check: Pass | MIT | |
| The Promotion Committeemohitagw15856/pm-claude-skills | 1.4k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Writing Livekit Scenarioslivekit-examples/agent-starter-python | 264 | 1 repos | ~2.5k | Automated safety check: Pass | MIT |
franklee16/academic-research-skills
A skill your agent uses when stress-testing NeurIPS experimental evidence, including baselines, ablations, data splits, compute, negative results, real-world use, and claim-to-evidence calibration.
mattnowdev/thinking-partner
A deterministic thinking partner that challenges assumptions and applies mental models to sharpen decisions, solve problems, and think more clearly.
CoWork-OS/CoWork-OS
Portfolio risk analysis including Value at Risk (parametric, historical, Monte Carlo), Conditional VaR, stress testing, drawdown analysis, and factor exposure assessment.
mohitagw15856/pm-claude-skills
Simulate the calibration meeting that discusses your promotion after your manager leaves the room — the debate, the packet's holes, the verdict.
livekit-examples/agent-starter-python
Creates and maintains the scenarios a LiveKit agent simulation runs, and wires the agent to consume them.
cxuu/golang-skills
A skill your agent uses when writing, reviewing, or improving Go test code — including table-driven tests, subtests, parallel tests, test helpers, test doubles, and assertions with cmp.Diff.
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running and reporting the analysis for an Annals of the American Association of Geographers manuscript — spatial statistics and modeling, remote-sensing accuracy, or…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when positioning an Annals of the American Association of Geographers manuscript in the literature — engaging geographic scholarship across the relevant area and the…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when responding to an Annals of the American Association of Geographers decision letter (major/minor revision) — building a point-by-point response to the subject editor and…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when defending the research design of an Annals of the American Association of Geographers manuscript — spatial/quantitative analysis and GIScience, remote-sensing and…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when you need to understand how the Annals of the American Association of Geographers evaluates a manuscript — double-anonymous review routed through a subject editor by…
brycewang-stanford/Awesome-Journal-Skills
A skill your agent uses when running the final pre-submission preflight for the Annals of the American Association of Geographers via ScholarOne Manuscripts — area/article-type selection…
Categories
A skill your agent uses when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark. Podc Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when building the evidence for an ACM PODC paper — where "evidence" is a proof, not a benchmark.
Podc Experiments fits situations like: building the evidence for an ACM PODC paper — where evidence is a proof; not a benchmark.
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill podc-experiments -a claude-code`. Or copy the skill folder (PODC-Skills/skills/podc-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/podc-experiments in your project. Claude Code loads it when a task matches its description.
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill podc-experiments -a codex`. Or copy the skill folder (PODC-Skills/skills/podc-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/podc-experiments in your project. Codex loads it when a task matches its description.
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 podc-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/podc-experiments, .gemini/skills/podc-experiments, .github/skills/podc-experiments and .opencode/skills/podc-experiments in your project.
SKILL.md names no scripts, command-line tools or credentials: Podc Experiments is instructions for the agent only.
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.
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.
Podc Experiments is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 5.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Podc Experiments: Neurips Experiments (franklee16/academic-research-skills, 223 stars), Thinking Partner (mattnowdev/thinking-partner, 206 stars), Risk Analyzer (CoWork-OS/CoWork-OS, 473 stars) and The Promotion Committee (mohitagw15856/pm-claude-skills, 1.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
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.
