Sandbox Bench
vercel/next.js
Benchmark React or Next.js changes on Vercel Sandbox VMs with paired A/B statistics: react PR/commit vs base, or Next.js PR/commit vs base, measured end-to-end through the bench/render-pipeline app…
Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles.
Install Hmt Results
$ npx skills add psu-efd/pyHMT2D --skill hmt-results -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install psu-efd/pyHMT2D hmt-results --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/psu-efd/pyHMT2D.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/hmt-results .claude/skills/hmt-results && 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 "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .claude/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-resultsType 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 psu-efd/pyHMT2D --skill hmt-results -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install psu-efd/pyHMT2D hmt-results --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/psu-efd/pyHMT2D.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/hmt-results .agents/skills/hmt-results && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .agents/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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 psu-efd/pyHMT2D --skill hmt-results -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install psu-efd/pyHMT2D hmt-results --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/psu-efd/pyHMT2D.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/hmt-results .cursor/skills/hmt-results && 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 "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .cursor/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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/psu-efd/pyHMT2D.git --path .agents/skills/hmt-results--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 psu-efd/pyHMT2D --skill hmt-results -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install psu-efd/pyHMT2D hmt-results --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/psu-efd/pyHMT2D.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/hmt-results .gemini/skills/hmt-results && 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 "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .gemini/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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 psu-efd/pyHMT2D hmt-resultsInstalls 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 psu-efd/pyHMT2D --skill hmt-results -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/psu-efd/pyHMT2D.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/hmt-results .github/skills/hmt-results && 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 "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .github/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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 psu-efd/pyHMT2D --skill hmt-results -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install psu-efd/pyHMT2D hmt-results --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/psu-efd/pyHMT2D.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/hmt-results .opencode/skills/hmt-results && 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 "hmt-results" agent skill from https://github.com/psu-efd/pyHMT2D/tree/main/.agents/skills/hmt-results into .opencode/skills/hmt-results/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "hmt-results", 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
hmt-results- GitHub stars
- 133
- Token cost
- ~478 tokens
- SKILL.md length
- 160 words
- Files
- 1
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- MIT
At a glance
Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles.
- Works in 4 steps: Find the result file. → Load the results. → Ask the user what they want to query.… → …
- Analyze simulation results
- SKILL.md covers Prerequisites and Steps
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Hmt Results is an agent skill from psu-efd/pyHMT2D. Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles. Use this when the user wants to read, query, probe, or analyze simulation results.
Its SKILL.md is about 480 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 Data & Analytics, covering Statistics. The repository describes itself as: Python Hydraulic Modeling Tools - 2D. The licence is MIT.
When your agent uses it
- Analyze simulation results
- Tasks that involve Statistics
Example prompts
- “/hmt-results”
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Find the result file.
- Load the results.
- Ask the user what they want to query. Offer these options
- Offer further queries or suggest /hmt-export to create VTK files.
What it can do on your machine
Read from SKILL.md and the folder at commit 57645ff. 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 bash).
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
Hmt Results loads about 478 tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 160 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 psu-efd/pyHMT2D at commit 57645ff, republished under its MIT licence (© psu-efd). 160 words, ~478 tokens.
Download SKILL.mdSave it as
.claude/skills/hmt-results/SKILL.md (or your agent's skills folder).- name
- hmt-results
- description
- Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles. Use this when the user wants to read, query, probe, or analyze simulation results.
Load simulation results and query values at points, domain-wide statistics, flood extent, or cross-section profiles.
Prerequisites
A project must be open. A result file (.h5 or .hdf) must exist.
Steps
Find the result file. Check
.hmt_session.jsonforresult_file. If not set, inspect any.h5/.hdffile:bash hmt-cli get_result_variables --args '{"result_file": "<path>"}'If multiple result files exist, ask the user which one to use.
Load the results.
bash hmt-cli read_results --args '{"result_file": "<path>", "timestep": -1}'Report: available variable names, number of time steps.
Ask the user what they want to query. Offer these options:
a) Value at a point — ask for x, y, variable name:
bash hmt-cli get_value_at_point --args '{"x": <x>, "y": <y>, "variable": "<var>"}'b) Domain-wide statistics — ask for variable name:
bash hmt-cli get_result_statistics --args '{"variable": "<var>"}'Report: min, max, mean, std, number of cells.
c) Flood extent — ask for depth threshold (default 0.01 m):
bash hmt-cli get_flood_extent --args '{"depth_threshold": <threshold>}'Report: flooded area in m² and km², percentage of domain flooded.
d) Cross-section profile — ask for two (x,y) endpoints and variable:
bash hmt-cli get_cross_section_profile --args '{"x1": <x1>, "y1": <y1>, "x2": <x2>, "y2": <y2>, "variable": "<var>", "n_points": 50}'Present as a table: Distance (m) | X | Y | Value.
Offer further queries or suggest
/hmt-exportto create VTK files.
© psu-efd, 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 .agents/skills/hmt-results of psu-efd/pyHMT2D.
Open the folder on GitHubat commit 57645ff
Compare with similar skills
Hmt Results 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 |
|---|---|---|---|---|---|---|
| Hmt Results this skillpsu-efd/pyHMT2D | 133 | — | ~478 | Automated safety check: Pass | MIT | |
| Sandbox Benchvercel/next.js | 143k | — | ~4.1k | Automated safety check: Pass | MIT | |
| Statistical Analysisspacering-net/codeg | 3.9k | 3 repos | ~5k | Automated safety check: Pass | MIT | |
| StatsmodelszLanqing/codex-claude-academic-skills | 4.7k | 15 repos | ~4.9k | Automated safety check: Pass | BSD-3-Clause | |
| AI Daily DigestvigorX777/ai-daily-digest | 1.6k | — | ~1.3k | Automated safety check: Pass | None | |
| Statistical Powerspacering-net/codeg | 3.9k | 1 repos | ~3.6k | Automated safety check: Notes | MIT |
Similar skills
- Official
Statistical Analysis
spacering-net/codeg
Guided statistical analysis for research data - test selection, assumption checking, effect sizes, power analysis, Bayesian alternatives, and APA-formatted reporting.
Statsmodels
zLanqing/codex-claude-academic-skills
Statistical models library for Python. An agent skill from zLanqing/codex-claude-academic-skills.
AI Daily Digest
vigorX777/ai-daily-digest
Fetches RSS feeds from 90 top Hacker News blogs (curated by Karpathy), uses AI to score and filter articles, and generates a daily digest in Markdown with Chinese-translated titles, category…
Statistical Power
spacering-net/codeg
Sample-size and statistical power calculations for planning studies.
Agent Session Monitor
higress-group/higress
Real-time agent conversation monitoring - monitors Higress access logs, aggregates conversations by session, tracks token usage.
More from psu-efd/pyHMT2D
All 9 skills in this repoHmt Convert
psu-efd/pyHMT2D
Convert between hydraulic model formats. An agent skill from psu-efd/pyHMT2D.
Hmt Calibrate
psu-efd/pyHMT2D
Run automated Manning's n calibration against observed water surface elevations using Bayesian optimization or Nelder-Mead.
Hmt Modify
psu-efd/pyHMT2D
Modify Manning's n roughness coefficients, inlet flow rates, or exit water surface elevations for the currently open pyHMT2D project and save the changes.
Hmt Monte Carlo
psu-efd/pyHMT2D
Run Monte Carlo uncertainty analysis on a hydraulic model by sampling parameters from statistical distributions and computing exceedance probabilities.
Hmt Open
psu-efd/pyHMT2D
Open a pyHMT2D hydraulic model project (SRH-2D or HEC-RAS) and display its materials, boundary conditions, and available result variables.
Hmt Export
psu-efd/pyHMT2D
Export simulation results and/or the computational mesh to VTK files for ParaView visualization.
Related
Categories
Questions about Hmt Results
What does Hmt Results do?
Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles. Hmt Results is an agent skill from psu-efd/pyHMT2D. Load simulation results and query values at specific points, domain-wide statistics, flood extent, or cross-section profiles.
When should I use Hmt Results?
Hmt Results fits situations like: analyze simulation results; tasks that involve Statistics.
How do I install Hmt Results in Claude Code?
Run `npx skills add psu-efd/pyHMT2D --skill hmt-results -a claude-code`. Or copy the skill folder (.agents/skills/hmt-results in psu-efd/pyHMT2D) into .claude/skills/hmt-results in your project. Claude Code loads it when a task matches its description.
How do I install Hmt Results in Codex?
Run `npx skills add psu-efd/pyHMT2D --skill hmt-results -a codex`. Or copy the skill folder (.agents/skills/hmt-results in psu-efd/pyHMT2D) into .agents/skills/hmt-results in your project. Codex loads it when a task matches its description.
Can I use Hmt Results 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 psu-efd/pyHMT2D --skill hmt-results -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/hmt-results, .gemini/skills/hmt-results, .github/skills/hmt-results and .opencode/skills/hmt-results in your project.
What does Hmt Results need to run?
SKILL.md names no scripts, command-line tools or credentials: Hmt Results is instructions for the agent only.
Does Hmt Results 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 Hmt Results 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 Hmt Results use?
Hmt Results 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 Hmt Results use?
About 478 tokens (SKILL.md is roughly 1.9k 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 Hmt Results?
Skills that share tags, products or a category with Hmt Results: Sandbox Bench (vercel/next.js, 143k stars), Statistical Analysis (spacering-net/codeg, 3.9k stars), Statsmodels (zLanqing/codex-claude-academic-skills, 4.7k stars) and AI Daily Digest (vigorX777/ai-daily-digest, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Hmt Results?
psu-efd (a GitHub user) maintains it in psu-efd/pyHMT2D, which has 133 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on August 9, 2026.
Source: psu-efd/pyHMT2D on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.