FAISS Similarity Search
Orchestra-Research/AI-Research-SKILLs
Sets up FAISS for fast nearest-neighbor search over large collections of dense vectors, choosing between Flat, IVF, HNSW and product quantization indexes.
A skill your agent uses when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers.
MITAuto-check passed
Install Parameters Random And Utilities
$ npx skills add VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill parameters-random-and-utilities --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/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .claude/skills/parameters-random-and-utilities && 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 "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .claude/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilitiesType 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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill parameters-random-and-utilities --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .agents/skills/parameters-random-and-utilities && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .agents/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill parameters-random-and-utilities --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .cursor/skills/parameters-random-and-utilities && 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 "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .cursor/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities--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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill parameters-random-and-utilities --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .gemini/skills/parameters-random-and-utilities && 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 "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .gemini/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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 VectorSpaceLab/AREX-Skill parameters-random-and-utilitiesInstalls 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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .github/skills/parameters-random-and-utilities && 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 "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .github/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill parameters-random-and-utilities --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities .opencode/skills/parameters-random-and-utilities && 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 "parameters-random-and-utilities" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities into .opencode/skills/parameters-random-and-utilities/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "parameters-random-and-utilities", 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
parameters-random-and-utilities- GitHub stars
- 331
- Token cost
- ~898 tokens
- SKILL.md length
- 300 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 157
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers.
- Works in 4 steps: Read references/parameters-and-rng.md… → Read… → Run scripts/smoke_parameters_and_data.py… → …
- Controlling imgaug stochastic parameters
- SKILL.md covers What this sub-skill covers, What it does not cover, Typical triggers and Fast path, plus 3 more sections
- Runs Python scripts from its folder
What it does
Parameters Random And Utilities is an agent skill from VectorSpaceLab/AREX-Skill. Use when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers.
Its SKILL.md is about 900 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `references/data-and-dtype-utilities.md`, `references/parameters-and-rng.md` and `references/troubleshooting.md`).
It works with NumPy. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is MIT.
When your agent uses it
- Controlling imgaug stochastic parameters
- Deterministic replay
- Dtype conversion
- Utility helpers
Example prompts
- “/parameters-random-and-utilities”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Read references/parameters-and-rng.md for stochastic parameters and reproducibility.
- Read references/data-and-dtype-utilities.md for dtype helpers, resizing, grids, and sample data.
- Run scripts/smoke_parameters_and_data.py to verify parameter sampling, quokka data, and dtype conversion.
- Read references/troubleshooting.md for NumPy 2, deprecations, dtype range, and display failures.
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. 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
Ships 1 file in scripts/ (Python), which the agent can run.
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
Parameters Random And Utilities loads about 898 tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 42 tokens; SKILL.md has 300 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); the scripts in this folder are not scanned.
SKILL.md
The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its MIT licence (© VectorSpaceLab). 300 words, ~898 tokens.
Download SKILL.mdSave it as
.claude/skills/parameters-random-and-utilities/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- parameters-random-and-utilities
- description
- Use when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- MIT
Parameters, Randomness, and Utilities
Use this sub-skill when the task is about how imgaug samples augmentation parameters, controls reproducibility, handles dtype/range conversion, loads built-in example data, or uses utility functions such as resizing, grids, and display helpers.
What this sub-skill covers
- Parameter shortcuts: scalar values,
(a, b)tuples, lists, andimgaug.parameters.StochasticParameterobjects. - Distribution objects such as
Choice,Uniform,Normal, andClip. - Seeds,
RNG, deterministic replay, and deprecatedrandom_state/deterministicAPI warnings. - Dtype conversion, clipping, range checks, and compatibility with current NumPy.
- Sample quokka images and annotations from
imgaug.data. - Utility helpers: resize, draw grids, and headless-safe visualization alternatives.
What it does not cover
- Building high-level image pipelines belongs to
../augmentation-pipelines/SKILL.md. - Constructing keypoints, boxes, dense maps, and mixed batches belongs to
../augmentables-and-batches/SKILL.md. - Background/multicore execution belongs to
../multicore-and-diagnostics/SKILL.md.
Typical triggers
- “How do tuple parameters work in imgaug?”
- “Make this imgaug pipeline reproducible.”
- “Why does imgaug warn about
random_state?” - “Use the built-in quokka image as a tiny fixture.”
- “Fix dtype clipping or NumPy import errors.”
Fast path
- Read
references/parameters-and-rng.mdfor stochastic parameters and reproducibility. - Read
references/data-and-dtype-utilities.mdfor dtype helpers, resizing, grids, and sample data. - Run
scripts/smoke_parameters_and_data.pyto verify parameter sampling, quokka data, and dtype conversion. - Read
references/troubleshooting.mdfor NumPy 2, deprecations, dtype range, and display failures.
Core parameter pattern
Many augmenter parameters accept flexible forms:
import imgaug.augmenters as iaa
import imgaug.parameters as iap
# Shortcut for a uniform blur range.
blur = iaa.GaussianBlur(sigma=(0.0, 3.0))
# Explicit stochastic distribution clipped to a safe range.
param = iap.Clip(iap.Normal(1.0, 0.1), 0.1, 3.0)
blur2 = iaa.GaussianBlur(sigma=param)Reproducibility pattern
Use a seed on an augmenter or convert a pipeline to deterministic form when the same sampled transform must be replayed.
seq = iaa.Sequential([iaa.Fliplr(0.5), iaa.Add((0, 5))], seed=1)
det = seq.to_deterministic()
out_a = det(images=images)
out_b = det(images=images)For aligned images and annotations, a single call containing every augmentable remains the safest pattern.
Utility warning signs
AttributeErrorinvolvingnp.sctypes: installnumpy<2for imgaug 0.4.0.- Unexpected clipping or rounding: inspect dtype helpers and value ranges before conversion.
- Display failure on a server: avoid
ia.imshow; write grids to image files instead. - Deprecation warnings around
random_stateordeterministic: preferseed,RNG, andto_deterministic()patterns.
© VectorSpaceLab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references) in skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/data-and-dtype-utilities.md
- references/parameters-and-rng.md
- references/troubleshooting.md
- scripts/smoke_parameters_and_data.py
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Parameters Random And Utilities 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 |
|---|---|---|---|---|---|---|
| Parameters Random And Utilities this skillVectorSpaceLab/AREX-Skill | 331 | — | ~898 | Automated safety check: Pass | MIT | |
| FAISS Similarity SearchOrchestra-Research/AI-Research-SKILLs | 13k | 6 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Tushare Datazillionare/zillionare | 321 | 2 repos | ~2.3k | Automated safety check: Pass | None | |
| 13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.2k | Automated safety check: Pass | MIT | |
| Python Performance Optimizationwshobson/agents | 40k | 13 repos | ~814 | Automated safety check: Pass | MIT | |
| Exploratory Data AnalysisOleafly/Oleafly | 212 | 2 repos | ~3.4k | Automated safety check: Notes | MIT |
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Works with
Questions about Parameters Random And Utilities
What does Parameters Random And Utilities do?
A skill your agent uses when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers. Parameters Random And Utilities is an agent skill from VectorSpaceLab/AREX-Skill. Use when controlling imgaug stochastic parameters, seeds, deterministic replay, dtype conversion, sample data, grids, or utility helpers.
When should I use Parameters Random And Utilities?
Parameters Random And Utilities fits situations like: controlling imgaug stochastic parameters; deterministic replay; dtype conversion; utility helpers.
How do I install Parameters Random And Utilities in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities in VectorSpaceLab/AREX-Skill) into .claude/skills/parameters-random-and-utilities in your project. Claude Code loads it when a task matches its description.
How do I install Parameters Random And Utilities in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a codex`. Or copy the skill folder (skills/repositories/repo-skills/imgaug/sub-skills/parameters-random-and-utilities in VectorSpaceLab/AREX-Skill) into .agents/skills/parameters-random-and-utilities in your project. Codex loads it when a task matches its description.
Can I use Parameters Random And Utilities 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 VectorSpaceLab/AREX-Skill --skill parameters-random-and-utilities -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/parameters-random-and-utilities, .gemini/skills/parameters-random-and-utilities, .github/skills/parameters-random-and-utilities and .opencode/skills/parameters-random-and-utilities in your project.
What does Parameters Random And Utilities need to run?
Going by SKILL.md and its folder, Parameters Random And Utilities needs Python for the scripts in its folder. Our summary lists: Python 3.
Does Parameters Random And Utilities 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 Parameters Random And Utilities 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Parameters Random And Utilities use?
Parameters Random And Utilities is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Parameters Random And Utilities use?
About 898 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. Its references folder adds about 1.6k tokens, read only when the agent opens those files.
What are the alternatives to Parameters Random And Utilities?
Skills that share tags, products or a category with Parameters Random And Utilities: FAISS Similarity Search (Orchestra-Research/AI-Research-SKILLs, 13k stars), Tushare Data (zillionare/zillionare, 321 stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars) and Python Performance Optimization (wshobson/agents, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Parameters Random And Utilities?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 331 GitHub stars. The repository holds 157 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.