Pine Backtester
TradersPost/pinescript-agents
Implements comprehensive backtesting and performance metrics.
A skill your agent uses when designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the…
Install Smr Simulation Studies
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-simulation-studies -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills smr-simulation-studies --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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .claude/skills/smr-simulation-studies && 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 "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .claude/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studiesType 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 smr-simulation-studies -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills smr-simulation-studies --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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .agents/skills/smr-simulation-studies && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .agents/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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 smr-simulation-studies -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills smr-simulation-studies --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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .cursor/skills/smr-simulation-studies && 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 "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .cursor/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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 Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies--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 smr-simulation-studies -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills smr-simulation-studies --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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .gemini/skills/smr-simulation-studies && 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 "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .gemini/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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 smr-simulation-studiesInstalls 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 smr-simulation-studies -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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .github/skills/smr-simulation-studies && 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 "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .github/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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 smr-simulation-studies -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 smr-simulation-studies --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/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies .opencode/skills/smr-simulation-studies && 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 "smr-simulation-studies" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies into .opencode/skills/smr-simulation-studies/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "smr-simulation-studies", 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
smr-simulation-studies- GitHub stars
- 1.2k
- Token cost
- ~1.2k tokens
- SKILL.md length
- 544 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 Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the…
- Designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes
- SKILL.md covers Design the DGP space…, The competitor set…, Metrics that match the claim and Presenting the study compactly, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Competing methods
What it does
Smr Simulation Studies is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the regimes where the method wins or breaks. Designs the simulation; does not derive properties or run the real-data illustration.
Its SKILL.md is about 1.2k 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 Business, Finance & HR, covering OKRs and executive reporting. 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 Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes
- Competing methods
- Performance metrics
- The regimes where the method wins
Example prompts
- “/smr-simulation-studies”
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
Smr Simulation Studies loads about 1.2k tokens when it runs. Until then it costs about 82 tokens; SKILL.md has 544 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). 544 words, ~1,176 tokens.
Download SKILL.mdSave it as
.claude/skills/smr-simulation-studies/SKILL.md (or your agent's skills folder).- name
- smr-simulation-studies
- description
- Use when designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the regimes where the method wins or breaks. Designs the simulation; does not derive properties or run the real-data illustration.
SMR Simulation Studies
Use this to build the Monte Carlo that an SMR reviewer will trust. At a methods journal the simulation is not a formality — it is the primary evidence that the analytical properties hold in finite samples and that the method beats real competitors. A weak or self-serving simulation sinks otherwise sound papers.
Design the DGP space deliberately
Reviewers attack the data-generating process first. Specify it as a designed experiment, not a convenient example:
- Factors and levels: sample size (and, for panels/networks, the relevant dimensions), the parameter that controls the difficulty (effect size, dependence, missingness rate, sparsity), and any nuisance complications. State why each level is realistic for sociological data.
- Coverage of the assumption boundary: include cells where your own assumptions fail, so the paper shows the method's limits, not just its triumphs. SMR rewards honesty about breakdown.
- Calibration to the application: at least one DGP should be calibrated to the real dataset in
smr-empirical-illustration, so the simulation speaks to a setting readers care about. - Replications and seeds: enough Monte Carlo replications for stable estimates of the metrics, with seeds fixed and reported for reproducibility.
The competitor set (non-negotiable)
A simulation that compares the new method only to a naive baseline is the classic reject. Include:
- The current default practitioners actually use.
- The strongest existing alternative for the same problem (often from a neighboring discipline —
see
smr-literature-positioning). - Where relevant, an oracle / infeasible benchmark to show the gap your method closes.
If your method loses to a competitor in some cell, report it and explain when each method is preferable — conditional recommendations are more credible than universal victory.
Metrics that match the claim
| Claim type | Report | Common SMR pitfall |
|---|---|---|
| Point estimation | bias, RMSE, relative efficiency | reporting bias but hiding variance |
| Inference / testing | empirical size, power, CI coverage and width | "performs well" with no coverage number |
| Selection / classification | accuracy + the costs of each error | accuracy only, ignoring imbalance |
| Computation | runtime, scaling, convergence rate | feasibility claim with no timing |
Coverage and size near the nominal level are the metrics SMR reviewers scrutinize most for inference methods — report the actual numbers, not adjectives.
Show full SKILL.md (193 more words)Show less
Presenting the study compactly
- Summarize the full grid in a table or a small-multiples figure; do not narrate every cell.
- Lead with the cell that makes the contribution's point (where the incumbent breaks and the method holds), then show the boundary where the method itself degrades.
- Hand the exhibit design to
smr-tables-figuresso the grid is self-contained and readable in print.
Checklist
- The DGP is specified as a factorial design with realistic levels, each justified.
- Cells where the method's own assumptions fail are included.
- At least one DGP is calibrated to the empirical illustration's data.
- The competitor set includes the current default and the strongest alternative.
- Metrics match each claim (coverage/size for inference, bias+variance for estimation).
- Replication count and seeds are reported.
- Cells where the method loses are reported with a conditional recommendation.
Anti-patterns
- Strawman comparison: only a naive baseline, never the real competitor.
- Sunny-cell selection: showing only regimes that favor the method.
- Adjective metrics: "good size control" with no rejection rates.
- Cherry-picked n: one favorable sample size with no scaling pattern.
- Uncalibrated fantasy DGP: a design unrelated to any sociological data.
- Hidden seeds / replication count: results that cannot be reproduced.
Output format
[Simulation status] convincing / needs repair / not ready
[DGP factors] <factor : levels, with realism note>
[Competitor set] <default + strongest alternative (+ oracle)>
[Metrics] <bias/RMSE/coverage/size/power/runtime as claimed>
[Boundary cell] <where the method degrades and why that is honest>
[Next SMR skill] smr-empirical-illustration© 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 Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Smr Simulation Studies 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 |
|---|---|---|---|---|---|---|
| Smr Simulation Studies this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.2k | Automated safety check: Pass | MIT | |
| Pine BacktesterTradersPost/pinescript-agents | 170 | 1 repos | ~3.9k | Automated safety check: Pass | None | |
| Analytics Strategyrampstackco/claude-skills | 941 | — | ~2.4k | Automated safety check: Pass | MIT | |
| Onboarding Plannerbpinheiroms/dotfiles | 108 | — | ~5.4k | Automated safety check: Pass | None | |
| Replit Decksanqiufong/slides-from-anything | 132 | 1 repos | ~2.9k | Automated safety check: Pass | Apache-2.0 | |
| Building Streamlit Dashboardsiusztinpaul/designing-real-world-ai-agents-workshop | 512 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 |
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Questions about Smr Simulation Studies
What does Smr Simulation Studies do?
A skill your agent uses when designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the…. Smr Simulation Studies is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes, competing methods, performance metrics, and the regimes where the method wins or breaks.
When should I use Smr Simulation Studies?
Smr Simulation Studies fits situations like: designing the Monte Carlo simulation study for a Sociological Methods & Research (SMR) paper — data-generating processes; competing methods; performance metrics; the regimes where the method wins.
How do I install Smr Simulation Studies in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-simulation-studies -a claude-code`. Or copy the skill folder (Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/smr-simulation-studies in your project. Claude Code loads it when a task matches its description.
How do I install Smr Simulation Studies in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill smr-simulation-studies -a codex`. Or copy the skill folder (Sociological-Methods-and-Research-Skills/skills/smr-simulation-studies in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/smr-simulation-studies in your project. Codex loads it when a task matches its description.
Can I use Smr Simulation Studies 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 smr-simulation-studies -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/smr-simulation-studies, .gemini/skills/smr-simulation-studies, .github/skills/smr-simulation-studies and .opencode/skills/smr-simulation-studies in your project.
What does Smr Simulation Studies need to run?
SKILL.md names no scripts, command-line tools or credentials: Smr Simulation Studies is instructions for the agent only.
Does Smr Simulation Studies 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 Smr Simulation Studies 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 Smr Simulation Studies use?
Smr Simulation Studies 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 Smr Simulation Studies use?
About 1.2k tokens (SKILL.md is roughly 4.7k 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 Smr Simulation Studies?
Skills that share tags, products or a category with Smr Simulation Studies: Pine Backtester (TradersPost/pinescript-agents, 170 stars), Analytics Strategy (rampstackco/claude-skills, 941 stars), Onboarding Planner (bpinheiroms/dotfiles, 108 stars) and Replit Deck (sanqiufong/slides-from-anything, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Smr Simulation Studies?
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.