Flowfile Build and Environment Setup
Edwardvaneechoud/Flowfile
Recreates every Flowfile development and build environment from scratch, with exact version pins and an explanation of what each Makefile target really does.
Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt /…
Install Capture Environment
$ npx skills add pedrohcgs/claude-code-my-workflow --skill capture-environment -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pedrohcgs/claude-code-my-workflow capture-environment --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/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/capture-environment .claude/skills/capture-environment && 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 "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .claude/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environmentType 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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pedrohcgs/claude-code-my-workflow capture-environment --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/capture-environment .agents/skills/capture-environment && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .agents/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pedrohcgs/claude-code-my-workflow capture-environment --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/capture-environment .cursor/skills/capture-environment && 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 "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .cursor/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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/pedrohcgs/claude-code-my-workflow.git --path .claude/skills/capture-environment--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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pedrohcgs/claude-code-my-workflow capture-environment --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/capture-environment .gemini/skills/capture-environment && 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 "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .gemini/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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 pedrohcgs/claude-code-my-workflow capture-environmentInstalls 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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/capture-environment .github/skills/capture-environment && 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 "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .github/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pedrohcgs/claude-code-my-workflow capture-environment --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pedrohcgs/claude-code-my-workflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/capture-environment .opencode/skills/capture-environment && 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 "capture-environment" agent skill from https://github.com/pedrohcgs/claude-code-my-workflow/tree/main/.claude/skills/capture-environment into .opencode/skills/capture-environment/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "capture-environment", 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
capture-environment- GitHub stars
- 1.7k
- Token cost
- ~2.8k tokens
- SKILL.md length
- 1,153 words
- Files
- 1
- Skills in repo
- 59
- Repo updated
- First seen
- Licence
- MIT
At a glance
Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt /…
- Works in 5 steps: Detect the stack → Capture per language → Dockerfile (only with --docker) → …
- User says capture the environment
- SKILL.md covers When to use, Inputs, Workflow and Output / artifacts, plus 3 more sections
- Calls uv, pip and python
What it does
Capture Environment is an agent skill from pedrohcgs/claude-code-my-workflow. Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt / environment.yml / uv.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block. Use when user says "capture the environment", "snapshot my dependencies", "pin the versions", "make a renv.lock /…
Its SKILL.md is about 2.8k 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 Research & Science, covering Econometrics and empirical research, Containers and Dependency management. It works with Docker and Python. The repository describes itself as: A ready-to-fork Claude Code template for academics using LaTeX/Beamer + R. Multi-agent review, quality gates, adversarial QA, and replication protocols. The licence is MIT.
When your agent uses it
- User says capture the environment
- Snapshot my dependencies
- Pin the versions
- Make a renv.lock / requirements.txt
Example prompts
- “Computational requirements”
- “capture the environment”
- “snapshot my dependencies”
- “/capture-environment”
Requirements
- Python 3
- Docker
- Pre-approved tools (allowed-tools): Read, Grep, Glob, Write, Bash
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit ae72617. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadGrepGlobWriteBash
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
uvpippythoncondaapt-getdocker
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
aeadataeditor.github.ioopenicpsr.org
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
Capture Environment loads about 2.8k tokens when it runs. Until then it costs about 162 tokens; SKILL.md has 1,153 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Grep, Glob, Write, Bash
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 pedrohcgs/claude-code-my-workflow at commit ae72617, republished under its MIT licence (© pedrohcgs). 1,153 words, ~2,799 tokens.
Download SKILL.mdSave it as
.claude/skills/capture-environment/SKILL.md (or your agent's skills folder).- name
- capture-environment
- description
- Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt / environment.yml / uv.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block. Use when user says "capture the environment", "snapshot my dependencies", "pin the versions", "make a renv.lock / requirements.txt", "make this byte-reproducible", or before releasing a replication package to openICPSR / the AEA Data Editor.
- allowed-tools
- Read, Grep, Glob, Write, Bash
- argument-hint
- [project-dir] [--docker] [--no-verify] (project-dir defaults to repo root)
- effort
- medium
/capture-environment — snapshot the computational environment
A replication package that runs on the author's laptop in 2026 and nowhere else in 2029 is not reproducible. This skill captures the exact computational environment — language versions, package versions, seeds, RNG kind, and (optionally) the OS layer — so a referee, the AEA Data Editor, or future-you can reconstruct it. It detects which stack the project uses and emits the artifacts that stack's ecosystem expects, then verifies the lockfile installs clean.
Core principle: Pin everything a result depends on. Display rounding aside, a re-run on a pinned environment should reproduce the paper to the replication-protocol.md tolerances — byte-identical when the optional Dockerfile is used.
When to use
- Before releasing a replication package to openICPSR, Zenodo, Dataverse, or a journal archive — the AEA Data Editor / DCAS standard expects a documented, version-pinned environment.
- Before submission, alongside
/audit-reproducibility— that skill checks the numbers; this one captures the environment those numbers were produced in (itssessionInfo.txtrequirement is satisfied by this skill). - After adding or upgrading a package mid-project — re-snapshot so the lockfile doesn't drift from what the code actually loads.
- When handing a project to a co-author or RA who needs to reconstruct your stack.
Inputs
$0— project directory. Defaults to the repo root. The skill looks underscripts/R/,scripts/stata/,scripts/python/.--docker— also emit aDockerfilepinning OS + language version + system libraries for byte-identical reproduction.--no-verify— skip Phase 3 (the best-effort clean-install check). Useful in CI or when the toolchain isn't installed locally.
Workflow
Phase 0: Detect the stack
Glob for stack signals and decide which capture paths to run (a project may be multi-language — DiD in R, an IV robustness check in Stata):
| Signal | Stack | Capture path |
|---|---|---|
scripts/R/*.R, DESCRIPTION, renv/, *.Rproj | R | renv + sessionInfo |
scripts/python/*.py, *.ipynb, pyproject.toml, requirements.txt, environment.yml, uv.lock | Python | pip / conda / uv |
scripts/stata/*.do | Stata | version + ado list |
If no signal is found, report and stop — there is no environment to capture.
Phase 1: Capture per language
R — emit two artifacts:
renv.lockviarenv::snapshot()(runrenv::init(bare = TRUE)first if the project isn't renv-managed; snapshot records every package + version + source/remote and the R version). Honors the seed conventions inr-code-conventions.md.sessionInfo.txtviaRscript -e "writeLines(capture.output(sessionInfo()), 'output/sessionInfo.txt')"— the human-readable companion/audit-reproducibilitylooks for.
Python — emit whichever matches the project's existing tooling (do not invent a new one):
uv.lock(preferred whenpyproject.toml+uvpresent — fully-resolved, hashed, cross-platform):uv lock/uv export --format requirements-txt > requirements.txt.requirements.txtviapip freeze(orpython -m pip freeze) for a venv/pip project — pin==exactly.environment.ymlviaconda env export --no-buildsfor a conda project. Always also record the interpreter version (python --version) in the report.
Stata — Stata has no lockfile, so capture the closest equivalents (mirrors stata-code-conventions.md §3):
- The pinned
versionline each.dofile declares (e.g.version 18) — grepscripts/stata/*.doand report the version actually pinned. - An ado/plus package inventory: a small
.dothat runswhichon the user-installed commands the pipeline uses (reghdfe,ivreg2,estout/esttab,rdrobust,csdid, …) plusado dirandabout, logged tooutput/sessionInfo_stata.txt. - A note that Stata version pinning is semantic (
version 18fixes command behavior), not a binary pin — the Dockerfile (Phase 2) cannot help here because Stata is licensed and not redistributable; record the exact Stata version + flavor (SE/MP/IC) + update level in the report so a replicator can match it.
Phase 1b: Record seeds and RNG
Grep the analysis scripts for the master seed and RNG kind so the "Computational requirements" block can state them:
- R:
set.seed(YYYYMMDD), andRNGkind()— flag"L'Ecuyer-CMRG"if parallel/Monte Carlo work is present (seesimulation-conventions.md). - Stata:
set seedandset sortseed. - Python:
numpy.random.default_rng(seed)/random.seed()/ framework seeds.
If the pipeline does randomized work (bootstrap, MC, RCT re-randomization, permutation inference) and no seed is found, surface it as a WARNING — an unseeded random result is not reproducible.
Phase 2: Dockerfile (only with --docker)
Emit a Dockerfile that pins the OS + language version + system libraries for byte-identical reproduction:
- R →
FROM rocker/r-ver:<X.Y.Z>(Rocker pins the R version),COPY renv.lock,RUN R -e "renv::restore()", plusapt-get installfor system libs the packages need (e.g.libcurl4-openssl-dev,libgdal-devfor spatial work). - Python →
FROM python:<X.Y.Z>-slim,COPY requirements.txt/uv.lock,RUN pip install -r requirements.txt(oruv sync --frozen). - Stata → cannot pin the licensed binary; emit a
Dockerfilestub that documents the expected Stata version + flavor and leaves thestatainstall/license step to the replicator (with a comment pointing at the AEA's guidance on Stata images).
Pin a digest where possible (FROM image@sha256:…) so the base image can't drift.
Show full SKILL.md (419 more words)Show less
Phase 3: Verify the lockfile installs clean (best-effort; skip with --no-verify)
Attempt a clean restore in a throwaway location and report PASS / FAIL — never overwrite the working environment:
- R:
renv::restore()into a temp library, orRscript -e "renv::status()"for a dry check. - Python:
uv sync --frozen/pip install --dry-run -r requirements.txtinto a fresh venv. - Docker (if
--docker):docker buildthe image.
A FAIL here means the lockfile references a package version that can't be resolved (yanked release, private remote, platform-specific wheel). Report it; do not auto-edit the lockfile.
Phase 4: Report
Print a paste-ready block and write it to output/computational_requirements.md:
## Computational requirements
**Software:** R 4.4.1 (or: Stata 18.0 SE, update 2026-01-15; Python 3.12.3)
**OS used:** macOS 15.5 (arm64) — Dockerfile pins Ubuntu 24.04 for portability
**Key packages:** fixest 0.12.1, did 2.1.2 (full list in renv.lock)
**Random seeds:** set.seed(20260609); RNGkind("L'Ecuyer-CMRG") for the bootstrap
**Approx. runtime:** [author confirms — e.g. ~12 min, 8 cores]
**Lockfiles in package:** renv.lock, output/sessionInfo.txt[, Dockerfile]Pre-fill software/package/seed lines from the captured artifacts; leave runtime for the author to confirm.
Output / artifacts
| Stack | Files written |
|---|---|
| R | renv.lock, output/sessionInfo.txt |
| Python | requirements.txt or environment.yml or uv.lock (matching project tooling) |
| Stata | output/sessionInfo_stata.txt (version + ado list; named so it does not overwrite R's in a mixed project) |
Any (--docker) | Dockerfile |
| Always | output/computational_requirements.md (the paste-ready block) |
Exit behavior
- All captures succeeded, verify PASS (or
--no-verify): exit 0, requirements block printed. - A missing-seed WARNING on a randomized pipeline: exit 0 with the warning surfaced — reproducibility is compromised but the snapshot still wrote.
- Verify FAIL (lockfile won't resolve): exit 1, so the skill can gate a pre-release
/commit. Report the unresolvable package; do not silently "fix" the lockfile. - No stack detected in Phase 0: exit 1 with the directories searched.
Cross-references
.claude/rules/replication-protocol.md— the tolerance contract a pinned environment is meant to reproduce..claude/rules/r-code-conventions.md— R seeding + output-path conventions this skill reads..claude/rules/stata-code-conventions.md— §3sessionInfo_stata.txt+version-pinning the Stata path mirrors..claude/rules/simulation-conventions.md— L'Ecuyer streams for reproducible parallel/MC work..claude/rules/confidential-data.md— when raw data is restricted, the environment still ships even though the data does not; coordinate the README's "data availability" section with this block./audit-reproducibility— consumes thesessionInfo.txtthis skill produces; run it after./data-analysis,/stata-replication,/simulation-study— the pipelines whose environment this snapshots.- AEA Data Editor checklist / openICPSR / DCAS — the external standards this skill targets.
What this skill does NOT do
- Re-run your analysis or check your numbers. It captures the environment;
/audit-reproducibilityverifies the manuscript's numeric claims against the outputs. - Package or de-identify data. Lockfiles describe software, not data. Disclosure avoidance, de-identification, and data-availability statements are out of scope — see
confidential-data.md. - Upgrade or "fix" your dependencies. It records what the code currently uses. If a verify FAIL surfaces a yanked version, you decide whether to pin an alternative.
- Pin a Stata binary. Stata is licensed and not redistributable; the skill records the exact version/flavor/update so a replicator can match it, but cannot containerize it.
© pedrohcgs, 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 .claude/skills/capture-environment of pedrohcgs/claude-code-my-workflow.
Open the folder on GitHubat commit ae72617
Compare with similar skills
Capture Environment 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 |
|---|---|---|---|---|---|---|
| Capture Environment this skillpedrohcgs/claude-code-my-workflow | 1.7k | — | ~2.8k | Automated safety check: Notes | MIT | |
| Flowfile Build and Environment SetupEdwardvaneechoud/Flowfile | 375 | — | ~7.3k | Automated safety check: Notes | MIT | |
| Megatron-LM Container and Dependency SetupNVIDIA/Megatron-LM | 18k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Minimegasandia-minimega/minimega | 160 | — | ~3.2k | Automated safety check: Pass | GPL-3.0-only | |
| Unraiddinglebear-ai/unraid | 135 | — | ~5.4k | Automated safety check: Notes | MIT | |
| Cyberowlaikarimhabush/cyberowl | 263 | — | ~2.5k | Automated safety check: Pass | MIT |
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Questions about Capture Environment
What does Capture Environment do?
Snapshot the computational environment for a replication package — detects the analysis stack (R / Stata / Python) and emits the right lockfiles (renv.lock + sessionInfo.txt, requirements.txt /…. Capture Environment is an agent skill from pedrohcgs/claude-code-my-workflow.lock, Stata version + ado package list), records seeds and RNG kind, optionally writes a pinning Dockerfile, and produces a paste-ready "Computational requirements" block.
When should I use Capture Environment?
Capture Environment fits situations like: user says capture the environment; snapshot my dependencies; pin the versions; make a renv.lock / requirements.txt.
How do I install Capture Environment in Claude Code?
Run `npx skills add pedrohcgs/claude-code-my-workflow --skill capture-environment -a claude-code`. Or copy the skill folder (.claude/skills/capture-environment in pedrohcgs/claude-code-my-workflow) into .claude/skills/capture-environment in your project. Claude Code loads it when a task matches its description.
How do I install Capture Environment in Codex?
Run `npx skills add pedrohcgs/claude-code-my-workflow --skill capture-environment -a codex`. Or copy the skill folder (.claude/skills/capture-environment in pedrohcgs/claude-code-my-workflow) into .agents/skills/capture-environment in your project. Codex loads it when a task matches its description.
Can I use Capture Environment 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 pedrohcgs/claude-code-my-workflow --skill capture-environment -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/capture-environment, .gemini/skills/capture-environment, .github/skills/capture-environment and .opencode/skills/capture-environment in your project.
What does Capture Environment need to run?
Going by SKILL.md and its folder, Capture Environment needs the command-line tools its instructions call (uv, pip, python, conda, apt-get and docker). Our summary lists: Python 3; Docker. Its frontmatter pre-approves these tools: Read, Grep, Glob, Write, Bash.
Does Capture Environment access the network?
SKILL.md names 2 domains. As links in the text: aeadataeditor.github.io and openicpsr.org. This is read from the text; nothing was executed.
Is Capture Environment safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Capture Environment use?
Capture Environment 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 Capture Environment use?
About 2.8k tokens (SKILL.md is roughly 11k 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 Capture Environment?
Skills that share tags, products or a category with Capture Environment: Flowfile Build and Environment Setup (Edwardvaneechoud/Flowfile, 375 stars), Megatron-LM Container and Dependency Setup (NVIDIA/Megatron-LM, 18k stars), Minimega (sandia-minimega/minimega, 160 stars) and Unraid (dinglebear-ai/unraid, 135 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Capture Environment?
pedrohcgs (a GitHub user) maintains it in pedrohcgs/claude-code-my-workflow, which has 1,653 GitHub stars. The repository holds 59 skills in this directory. The repository was last updated on September 27, 2026.
Source: pedrohcgs/claude-code-my-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.