Excel and CSV Data Analysis
bytedance/deer-flow
Analyzes uploaded Excel and CSV files with SQL through DuckDB, producing schema inspections, statistical summaries and exports to CSV, JSON or Markdown.
Wire up how an artifact renders in LAVA, end to end across the producer and the viewer.
MITAuto-check passed
Install Lava Data View
$ npx skills add abrignoni/VLEAPP --skill lava-data-view -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install abrignoni/VLEAPP lava-data-view --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/abrignoni/VLEAPP.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/lava-data-view .claude/skills/lava-data-view && 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 "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .claude/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-viewType 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 abrignoni/VLEAPP --skill lava-data-view -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install abrignoni/VLEAPP lava-data-view --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/abrignoni/VLEAPP.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/lava-data-view .agents/skills/lava-data-view && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .agents/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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 abrignoni/VLEAPP --skill lava-data-view -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install abrignoni/VLEAPP lava-data-view --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/abrignoni/VLEAPP.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/lava-data-view .cursor/skills/lava-data-view && 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 "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .cursor/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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/abrignoni/VLEAPP.git --path .claude/skills/lava-data-view--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 abrignoni/VLEAPP --skill lava-data-view -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install abrignoni/VLEAPP lava-data-view --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/abrignoni/VLEAPP.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/lava-data-view .gemini/skills/lava-data-view && 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 "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .gemini/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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 abrignoni/VLEAPP lava-data-viewInstalls 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 abrignoni/VLEAPP --skill lava-data-view -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/abrignoni/VLEAPP.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/lava-data-view .github/skills/lava-data-view && 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 "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .github/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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 abrignoni/VLEAPP --skill lava-data-view -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install abrignoni/VLEAPP lava-data-view --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/abrignoni/VLEAPP.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/lava-data-view .opencode/skills/lava-data-view && 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 "lava-data-view" agent skill from https://github.com/abrignoni/VLEAPP/tree/main/.claude/skills/lava-data-view into .opencode/skills/lava-data-view/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "lava-data-view", 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
lava-data-view- GitHub stars
- 118
- Token cost
- ~1.1k tokens
- SKILL.md length
- 570 words
- Files
- 1
- Skills in repo
- 5
- Repo updated
- First seen
- Licence
- MIT
At a glance
Wire up how an artifact renders in LAVA, end to end across the producer and the viewer.
- Works in 4 steps: Producer: declare the view → Make sure the columns survive the trip → Viewer: only if the type or a field is new → …
- Adding a conversation view to an artifact
- SKILL.md covers The change is always two-sided, 1. Producer: declare the view, 2. Make sure the columns… and 3. Viewer: only if the type or…, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Lava Data View is an agent skill from abrignoni/VLEAPP. Wire up how an artifact renders in LAVA, end to end across the producer and the viewer. Use when adding a conversation view to an artifact, when a view renders wrong or not at all, when adding a field to the LAVA schema or manifest, or when asked to "add a module to the LAVA schema".
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with SQL. The repository describes itself as: Vehicle Logs Events And Properties Parser. The licence is MIT.
When your agent uses it
- Adding a conversation view to an artifact
- A view renders wrong
- Adding a field to the LAVA schema
- Asked to add a module to the LAVA schema
Example prompts
- “add a module to the LAVA schema”
- “/lava-data-view”
Workflow steps
4 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 eada9a9. 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.
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
Lava Data View loads about 1.1k tokens when it runs. Until then it costs about 75 tokens; SKILL.md has 570 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 abrignoni/VLEAPP at commit eada9a9, republished under its MIT licence (© abrignoni). 570 words, ~1,080 tokens.
Download SKILL.mdSave it as
.claude/skills/lava-data-view/SKILL.md (or your agent's skills folder).- name
- lava-data-view
- description
- Wire up how an artifact renders in LAVA, end to end across the producer and the viewer. Use when adding a conversation view to an artifact, when a view renders wrong or not at all, when adding a field to the LAVA schema or manifest, or when asked to "add a module to the LAVA schema".
<!-- SHARED SKILL. Canonical copy lives in the LAVA repo under .claude/skills/.
Do not edit in place; edit the canonical copy and re-run the sync script. -->Adding or changing a LAVA data view
LAVA/docs/schema/ is the authority and is more current than any summary:
| doc | covers |
|---|---|
docs/schema/data-views.md | every view type and every config field, with a required/optional table |
docs/schema/output-data-v1.md | the _lava_data manifest structure |
docs/schema/sqlite-data-v1.md | the artifact database layout |
Read data-views.md before writing a data_views block. This skill is the order of
operations and the traps around it.
The change is always two-sided
The extractor declares the view; LAVA renders it. A change to one half without the other either does nothing or breaks the case. Decide up front which halves you are touching, and say so in the PR.
Producer side (any of the five extractors): the data_views block in
__artifacts_v2__, plus whatever columns the view references.
Viewer side (LAVA): only needed for a genuinely new view type or a new config field. An existing view type with a new artifact needs no LAVA change at all.
1. Producer: declare the view
Column values in the config are the display names as they appear in the artifact module, not the sanitized SQL names. LAVA resolves them, and also accepts an exact match on the sanitized form, so use the display name and stay consistent.
Every required field in data-views.md must be present. A conversation view missing
directionColumn or timeColumn does not degrade gracefully, it fails to group.
directionSentValue is the value meaning "sent", and it is type-sensitive: 1 and "1"
are not interchangeable. Confirm what your parser actually writes into that column.
2. Make sure the columns survive the trip
The table is created from the artifact's headers, and column names are sanitized to
snake_case, so Chat_Contact_ID becomes chat_contact_id. A header typed
('X', 'datetime') becomes an INTEGER epoch column.
Headers that sanitize to SQL reserved words are handled by quote_sql_name(), but a header
that sanitizes to the same name as another column silently collides. Check for that when
adding columns to an artifact that already has a view.
If the view references media, see the lava-media rule: register with check_in_media and
set mediaColumn.
Show full SKILL.md (233 more words)Show less
3. Viewer: only if the type or a field is new
data_views is consumed in src/renderer/components/ by ArtifactView.jsx, which decides
whether the view is offered, and ConversationPanel.jsx / ConversationExportView.jsx,
which render it. A new field means touching the panel and the export view together, or the
on-screen view and the exported one disagree.
Note the legacy alias: the code reads data_views.conversation || data_views.chat and has
a separate branch for chat. New artifacts use conversation. Do not add chat, and do
not remove support for it.
4. Verify by opening a real case
LAVA has no automated test runner. A passing harness is necessary and not sufficient, because the harness cannot exercise the GUI, which is where view bugs live.
Run an actual extractor against real data, then open the resulting _lava_data.lava in the
running app and check: the view is offered at all, conversations group on the right column,
direction is right for both sent and received, ordering follows timeColumn, labels resolve
rather than showing raw identifiers, and media renders in the bubble.
Confirm the plain table view still works. It is the default for every artifact and is easy to break while adding a second view.
Known stale documentation
docs/schema/sqlite-data-v1.md says the artifact table is named from the artifact's name
value. It is not. lava_process_artifact derives it from func_name, and falls back to
artifact_name only for modules that predate that parameter. Trust the code.
© abrignoni, 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/lava-data-view of abrignoni/VLEAPP.
Open the folder on GitHubat commit eada9a9
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders. This page covers the copy in abrignoni/VLEAPP, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Lava Data View 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 |
|---|---|---|---|---|---|---|
| Lava Data View this skillabrignoni/VLEAPP | 118 | — | ~1.1k | Automated safety check: Pass | MIT | |
| Excel and CSV Data Analysisbytedance/deer-flow | 83k | 4 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Clickhouse Logs Queriessupabase/supabase | 111k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Review PRapache/shardingsphere | 21k | — | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Django Filter Benchmarksaleor/saleor | 23k | — | ~2.3k | Automated safety check: Pass | BSD-3-Clause | |
| Geoflowyaojingang/GEOFlow | 3.8k | — | ~722 | Automated safety check: Pass | AGPL-3.0 |
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Works with
Questions about Lava Data View
What does Lava Data View do?
Wire up how an artifact renders in LAVA, end to end across the producer and the viewer. Lava Data View is an agent skill from abrignoni/VLEAPP. Wire up how an artifact renders in LAVA, end to end across the producer and the viewer.
When should I use Lava Data View?
Lava Data View fits situations like: adding a conversation view to an artifact; A view renders wrong; adding a field to the LAVA schema; asked to add a module to the LAVA schema.
How do I install Lava Data View in Claude Code?
Run `npx skills add abrignoni/VLEAPP --skill lava-data-view -a claude-code`. Or copy the skill folder (.claude/skills/lava-data-view in abrignoni/VLEAPP) into .claude/skills/lava-data-view in your project. Claude Code loads it when a task matches its description.
How do I install Lava Data View in Codex?
Run `npx skills add abrignoni/VLEAPP --skill lava-data-view -a codex`. Or copy the skill folder (.claude/skills/lava-data-view in abrignoni/VLEAPP) into .agents/skills/lava-data-view in your project. Codex loads it when a task matches its description.
Can I use Lava Data View 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 abrignoni/VLEAPP --skill lava-data-view -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lava-data-view, .gemini/skills/lava-data-view, .github/skills/lava-data-view and .opencode/skills/lava-data-view in your project.
What does Lava Data View need to run?
SKILL.md names no scripts, command-line tools or credentials: Lava Data View is instructions for the agent only.
Does Lava Data View 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 Lava Data View 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 Lava Data View use?
Lava Data View 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 Lava Data View use?
About 1.1k tokens (SKILL.md is roughly 4.3k 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 Lava Data View?
Skills that share tags, products or a category with Lava Data View: Excel and CSV Data Analysis (bytedance/deer-flow, 83k stars), Clickhouse Logs Queries (supabase/supabase, 111k stars), Review PR (apache/shardingsphere, 21k stars) and Django Filter Benchmark (saleor/saleor, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Lava Data View?
abrignoni (a GitHub user) maintains it in abrignoni/VLEAPP, which has 118 GitHub stars. The repository holds 5 skills in this directory. The repository was last updated on October 7, 2026.
Source: abrignoni/VLEAPP on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.