Sync Upstream
nyaruka/phonenumbers
Sync this Go port with a new upstream google/libphonenumber release — regenerate the embedded metadata and reconcile the ported Java logic.
A skill your agent uses when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon…
Install Micro Experiments
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill micro-experiments -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills micro-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/MICRO-Skills/skills/micro-experiments .claude/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .claude/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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/MICRO-Skills/skills/micro-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 micro-experiments -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills micro-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/MICRO-Skills/skills/micro-experiments .agents/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .agents/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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 micro-experiments -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills micro-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/MICRO-Skills/skills/micro-experiments .cursor/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .cursor/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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 MICRO-Skills/skills/micro-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 micro-experiments -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills micro-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/MICRO-Skills/skills/micro-experiments .gemini/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .gemini/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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 micro-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 micro-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/MICRO-Skills/skills/micro-experiments .github/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .github/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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 micro-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 micro-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/MICRO-Skills/skills/micro-experiments .opencode/skills/micro-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 "micro-experiments" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/MICRO-Skills/skills/micro-experiments into .opencode/skills/micro-experiments/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "micro-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
micro-experiments- GitHub stars
- 1.2k
- Token cost
- ~1.6k tokens
- SKILL.md length
- 677 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon…
- Tuning baselines the PC will respect
- SKILL.md covers The instrument ladder, Baseline construction — where…, Workloads and The ablation and sensitivity…, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Selecting workload suites
What it does
Micro Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon, tuning baselines the PC will respect, selecting workload suites, running ablations and sensitivity sweeps, and reporting geomeans with full overhead accounting.
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 Business, Finance & HR, covering Accounting and bookkeeping. 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
- Tuning baselines the PC will respect
- Selecting workload suites
- Running ablations and sensitivity sweeps
- Reporting geomeans with full overhead accounting
Example prompts
- “/micro-experiments”
Requirements
- Python 3
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 python).
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
Micro Experiments loads about 1.6k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 677 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). 677 words, ~1,619 tokens.
Download SKILL.mdSave it as
.claude/skills/micro-experiments/SKILL.md (or your agent's skills folder).- name
- micro-experiments
- description
- Use when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon, tuning baselines the PC will respect, selecting workload suites, running ablations and sensitivity sweeps, and reporting geomeans with full overhead accounting.
MICRO Experiments
MICRO's evaluation culture is instrument-centric: the community knows exactly what each measurement tool can and cannot prove, and reviewers score the match between claim and instrument before they look at the numbers.
The instrument ladder
| Instrument | Proves | Cannot prove | Typical tools |
|---|---|---|---|
| Analytical / trace model | First-order potential, limit studies | Interaction effects, timing | custom, trace-driven models |
| Cycle-level simulation | Relative performance of mechanisms | Absolute wall-clock, physical cost | gem5, ChampSim, Sniper, Ramulator/DRAMsim3 |
| Power/area models on top of sim | Energy and area trends | Sign-off-quality numbers | McPAT, CACTI, Accelergy |
| RTL + synthesis | Timing closure, real area/power at a node | Full-system performance | Verilog/Chisel + synthesis flow |
| FPGA prototype | Functional correctness at scale, OS interaction | ASIC frequency/power | FireSim, custom boards |
| Silicon measurement | Everything, for that one chip | Generality across designs | perf counters, power rails |
Rule: claim one rung below your strongest instrument. Cycle-level simulation plus McPAT supports "reduces memory-stall cycles by X% with ~Y mm² estimated overhead"; it does not support "improves datacenter TCO." The lineage here is the venue's own: CACTI 6.0 (MICRO 2007) and McPAT (MICRO 2009) were published at MICRO precisely because the community polices modeling fidelity.
Baseline construction — where most rejections start
- The baseline core must be configured like a current product, not a textbook default: wide OoO, capable branch predictor, competent multi-stream prefetcher, realistic DRAM timing. A win over gem5's out-of-the-box config is a non-result.
- Include the best prior mechanism in your exact category, re-implemented in your simulator with its published parameters — not just numbers copied from its paper under a different config.
- Add an idealized upper bound (oracle predictor, infinite table) so readers see what fraction of the headroom you capture.
- If your mechanism uses N KB of extra storage, give the baseline the same N KB as additional cache/predictor capacity in at least one comparison — the "iso-storage" check reviewers ask for in rebuttal anyway.
Workloads
- Name the suite and the subsetting rule: SPEC CPU2017 (all, or a stated-criterion subset), PARSEC/GAP for multithreaded, MLPerf or named DNNs for accelerators, plus the domain traces your mechanism targets.
- Disclose sampling methodology: SimPoint regions, warmup lengths, instruction budgets per region. Cherry-picked "representative regions" without a stated selection rule are a rebuttal magnet.
- Report per-workload bars plus geomean — never arithmetic means of speedups, and never geomean-only (it hides the regressions reviewers will hunt for).
# the only defensible summary statistic for speedups
from math import prod
def geomean(xs):
return prod(xs) ** (1.0 / len(xs))
speedups = per_workload_ipc_new / per_workload_ipc_base # elementwise
print(f"geomean {geomean(list(speedups)):.3f}, "
f"min {min(speedups):.3f} ({worst_workload}), "
f"regressions: {(speedups < 1.0).sum()} of {len(speedups)}")Show full SKILL.md (299 more words)Show less
The ablation and sensitivity contract
Every design decision named in the mechanism section owes the evaluation section a figure or table row:
- Ablate each component (drop the filter, halve the table, disable the guard) to show each earns its area.
- Sweep the structural parameters: table sizes, associativities, thresholds, core counts, LLC capacities, DRAM bandwidth. The mechanism should degrade gracefully at the sweep edges — cliffs demand explanation in the text.
- Stress adversarially: the workload class the mechanism should not help, the access pattern designed to defeat it. Reporting a bounded loss builds more trust than an unbroken win column.
Simulation-length and validation sanity
Two credibility checks reviewers apply that authors often skip:
- Enough simulated instructions per region. Sub-100M-instruction detailed windows on memory-bound workloads mostly measure the warmup transient. State warmup and detailed lengths, and show at least once that doubling them does not move the headline.
- Baseline validation against published numbers. Before trusting relative results, show your baseline's absolute behavior is sane: IPC or MPKI within the published envelope for the same suite and a comparable config. A baseline whose branch predictor achieves 2x the published MPKI of the modeled design invalidates the comparison silently.
For multicore results, disclose how heterogeneity was handled: mix construction rule, per-mix repetitions, and whether throughput is weighted speedup, harmonic mean, or raw IPC sum — each answers a different question and reviewers check that the metric matches the claim (fairness claims need a fairness metric).
Overhead accounting checklist
- Storage: bits/entry × entries, totaled in KB, per core and shared.
- Area and power: model named with version (e.g., McPAT vX at Ynm), numbers labeled as estimates.
- Latency: added pipeline stages or access-path cycles; off critical path claims justified.
- Energy: dynamic + leakage deltas, not just "negligible."
- Complexity: verification surface, new SRAM ports, wiring — one honest paragraph.
Output format
[Instrument] <rung used> — claim height matches: yes / no (quote the overclaim)
[Baseline strength] product-like config / best-prior reimplemented / oracle bound /
iso-storage check: present-absent each
[Workloads] suite + subset rule + sampling disclosure: complete / gaps listed
[Summary stats] per-workload + geomean + regression count: yes / no
[Ablations] each mechanism component covered: list of unablated components
[Sensitivity] parameters swept vs parameters hardcoded
[Overheads] storage / area / power / latency / energy: quantified-missing each© 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 MICRO-Skills/skills/micro-experiments of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Micro 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 |
|---|---|---|---|---|---|---|
| Micro Experiments this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.6k | Automated safety check: Pass | MIT | |
| Sync Upstreamnyaruka/phonenumbers | 1.6k | — | ~2.8k | Automated safety check: Pass | MIT | |
| Longbridge Value Investinghelsome/folio | 269 | 2 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Radiology Tablehuang-sir1/radiology-skills | 1.9k | — | ~1.3k | Automated safety check: Pass | Custom licence | |
| Odoo Agency Fleet Reviewerpipe-org/mcp-odoo | 420 | — | ~699 | Automated safety check: Pass | MIT | |
| Beancount Closebex-co/beancount-io | 295 | — | ~1.4k | Automated safety check: Pass | MIT |
Similar skills
Longbridge Value Investing
helsome/folio
Value investing analysis using Graham (NCAV/net-net/defensive-investor) and Buffett (economic moat/ROE/FCF) methodologies.
Radiology Table
huang-sir1/radiology-skills
Create/audit editable publication tables with source reconciliation; not figures or statistical inference.
Odoo Agency Fleet Review
erpipe-org/mcp-odoo
Review many client Odoo databases at once through odoo-mcp's cross-instance tools — fleet-wide accounting health, per-client aging, partial-failure triage — for agencies and partners managing 5–50…
Beancount Close
bex-co/beancount-io
Close an accounting period in a Beancount ledger by reconciling each active account through beancount-reconcile, checking assertions and recurring gaps, reviewing flags, then proposing a commit with…
ERPClaw ERP Controller
avansaber/erpclaw
Operates the ERPClaw self-hosted ERP in plain language: accounting, invoicing, inventory, purchasing, tax, HR, payroll and reports, treating the ERP as the single source of truth.
More from brycewang-stanford/Awesome-Journal-Skills
All 2,387 skills in this repoAaag Data Analysis
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…
Aaag Literature Positioning
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…
Aaag Rebuttal
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…
Aaag Research Design
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…
Aaag Review Process
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…
Aaag Submission
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…
Related
Categories
Questions about Micro Experiments
What does Micro Experiments do?
A skill your agent uses when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon…. Micro Experiments is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when designing or auditing the evaluation of a MICRO paper — choosing the right instrument on the ladder from analytical model to cycle-level simulator to RTL to silicon, tuning baselines the PC will respect, selecting workload suites, running ablations and sensitivity sweeps, and reporting geomeans with full overhead accounting.
When should I use Micro Experiments?
Micro Experiments fits situations like: tuning baselines the PC will respect; selecting workload suites; running ablations and sensitivity sweeps; reporting geomeans with full overhead accounting.
How do I install Micro Experiments in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill micro-experiments -a claude-code`. Or copy the skill folder (MICRO-Skills/skills/micro-experiments in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/micro-experiments in your project. Claude Code loads it when a task matches its description.
How do I install Micro Experiments in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill micro-experiments -a codex`. Or copy the skill folder (MICRO-Skills/skills/micro-experiments in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/micro-experiments in your project. Codex loads it when a task matches its description.
Can I use Micro 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 micro-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/micro-experiments, .gemini/skills/micro-experiments, .github/skills/micro-experiments and .opencode/skills/micro-experiments in your project.
What does Micro Experiments need to run?
SKILL.md names no scripts, command-line tools or credentials: Micro Experiments is instructions for the agent only. Our summary lists: Python 3.
Does Micro 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 Micro 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 Micro Experiments use?
Micro 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 Micro Experiments use?
About 1.6k tokens (SKILL.md is roughly 6.5k 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 Micro Experiments?
Skills that share tags, products or a category with Micro Experiments: Sync Upstream (nyaruka/phonenumbers, 1.6k stars), Longbridge Value Investing (helsome/folio, 269 stars), Radiology Table (huang-sir1/radiology-skills, 1.9k stars) and Odoo Agency Fleet Review (erpipe-org/mcp-odoo, 420 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Micro Experiments?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,219 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.