Update installed SenseNova Skills in OpenClaw or hermes-agent, either as a complete bundle or as selected skills. Compare versions before replacing files, back up existing installations, and report which skills changed or were already current.
中文简介正在准备中。当前显示英语简介。
Update SenseNova Skills (the sn-* bundle) inside an OpenClaw or hermes-agent install. ALWAYS use this skill when the user says any of: "update SenseNova skills", "update SN skills", "更新 sensenova skills", "更新 sn skills", "刷新 sn-*", "升级 sn-* skills", or names a specific sn-* skill to update (e.g. "更新 sn-ppt-standard", "refresh sn-image-base"). Default scope is the whole sn-* bundle; if the user names specific skills, update ONLY those.
安装前可以查看交给 AI 代理的指令内容。
Refresh installed sn-* skills from upstream
SenseNova-Skills.
sn-* skill upstream.Check which directories exist:
~/.openclaw/skills/ | ~/.hermes/skills/ | Target |
|---|---|---|
| exists | absent | openclaw |
| absent | exists | hermes |
| exists | exists | ask the user — never silently dual-write |
| absent | absent | no install found, stop |
Persistent cache at ~/.cache/sn-update/repo/. Default URL:
https://github.com/OpenSenseNova/SenseNova-Skills.git. User may override
with a fork URL.
--filter=blob:none --no-checkout, then sparse-checkout only
the selected skills/<name> paths before copying them. --filter=blob:none
alone does not keep the cache small if the full worktree is checked out;
that checkout will still download most or all needed blobs. It still
preserves history metadata for SHA queries.skills/<name> paths before
copying. If updating the whole sn-* bundle, expect most/all skill blobs to
be downloaded.origin differs from the requested URL,
delete and re-clone.For each skill, pick the highest-precedence signal present on both sides (installed + upstream); equal → skip, differ → install.
Upstream "version" is the per-subtree commit SHA — using repo HEAD would mark unrelated skills as stale every time:
git -C <cache> log -1 --format=%H -- skills/<skill-name>
.sn-version marker: one-line file inside the installed skill
holding the SHA from its last install..sn-release marker (fallback): one-line file holding the
upstream tag name. Compare against git describe --tags --abbrev=0.version: field in SKILL.md frontmatter: parse from
YAML on both sides, but only for forks or skills that explicitly add this
field. If either side lacks it, C does not apply.Always write .sn-version on install so future runs can use A.
For each skill flagged "install":
<agent-skills>/<skill-name>/ into a
single timestamped backup bucket shared by all skills in this run:
~/.<agent>/skills_backup/<UTC-timestamp>/<skill-name>/
(e.g. 2026-04-30T15-29-07Z).<cache>/skills/<skill-name>/ → <agent-skills>/<skill-name>/.
Never symlink (ln -s) from the cache. The cache lives under
~/.cache/ with permissions the agent runtime may not be able to
traverse, and some runtimes refuse to load skills resolved through
symlinks. Always do a real recursive copy so the installed tree is
self-contained and owned by the agent skills dir..sn-version with the upstream subtree SHA inside the new copy.If the bucket ends up empty (all targets were fresh installs), remove it.
The backup tree is a sibling of skills/, never a .bak folder
inside it — most agent runtimes scan the whole skills/ directory and
would pick up stale duplicates.
After every run, prune the per-agent backup root to at most 3 buckets. Timestamps sort lexicographically; keep the newest 3, delete the rest. Run this even when the current run produced no backup of its own.
Group by status, keep it short:
Updated (3): sn-ppt-standard, sn-image-base, sn-deep-research
Already up-to-date (5): sn-ppt-creative, sn-ppt-doctor, ...
Backup: ~/.openclaw/skills_backup/2026-04-30T15-29-07Z/
Backup: when nothing was backed up.abc1234 → def5678) only if the user asks for detail.~/.<agent>/skills_backup/ if they want to roll back.sn-update updating itself — fine; the new copy takes effect on
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Compare counts and shares for two categories in Excel data. The skill cleans the selected columns, calculates differences and percentages, and produces a summary spreadsheet plus bar and pie charts.
中文简介正在准备中。当前显示英语简介。
Analyze Excel data using custom categories, count distributions, and compare groups with charts. Score text using its length, technical terms, numbers, and selected complex concepts, then visualize difficulty levels and the relationship between text length and scores.
中文简介正在准备中。当前显示英语简介。
Count categories in a chosen data column after removing missing values and placeholder labels. Calculate each category’s share and create high-resolution charts combining counts, percentages, pie charts, and horizontal bars for distribution reports.
中文简介正在准备中。当前显示英语简介。
Clean category and numeric fields in structured data, compare groups with counts and cross-tabulations, and produce charts, Excel results, and a Markdown report. Export visuals as high-resolution PNG and SVG files for use in reports.
中文简介正在准备中。当前显示英语简介。
Filter Excel data using candidate column names, RGB color values, text prefixes, and regular expressions, which match text patterns. Calculate totals and averages, then export results to Excel with highlighted rows and a download link.
中文简介正在准备中。当前显示英语简介。
Filter rows from Excel or previously converted Parquet files, a format designed for efficient data storage. Summarize matching records by group with counts, percentages, and totals, then export the summary to Excel.
中文简介正在准备中。当前显示英语简介。