Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a…

Apache-2.0Auto-check passedDocuments & Office

Install Editaplot

skills CLI
$ npx skills add liushunqi8-hash/editaplot2026 --skill editaplot -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install liushunqi8-hash/editaplot2026 editaplot --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
editaplot
GitHub stars
128
Token cost
~5.8k tokens
SKILL.md length
2,938 words
Files
710 (incl. assets)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a…

  • Works in 12 steps: Reject unsupported platforms before… → Locate editaplot.cmd in the installed… → Require the complete repository for… → …
  • Beginner drop in a file and draw it requests
  • SKILL.md covers Request only scoped Windows…, Start with the beginner path, Keep scientific decisions with… and Apply the publication-informed…, plus 2 more sections
  • Calls winget

What it does

Editaplot is an agent skill from liushunqi8-hash/editaplot2026. Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a callable local Origin/OriginPro installation on physical Windows 10/11 x64. Use for beginner “drop in a file and draw it” requests; XPS, XRD, XAS, PL/TRPL, DSC, NMR, FTIR/IR, UV-Vis, electrochemistry, medical/AI evidence, distribution, relationship, error-bar, bar, stacked, pie, Sankey, radar, heatmap, or verified 3D…

Its SKILL.md is about 5.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 711 other files, including assets (for example `ASSET_PROVENANCE.md`, `AUTHORS.md` and `CHANGELOG.md`).

It sits in Documents & Office, covering Excel spreadsheets and CSV and tabular files. It works with Python, Windows, Microsoft Excel and Linux. The repository describes itself as: EditaPlot — editable Origin/OriginPro scientific plotting skill, with Origin 2026 (10.30) compatibility fixes. The licence is Apache-2.0.

When your agent uses it

  • Beginner drop in a file and draw it requests
  • Electrochemistry
  • Medical/AI evidence
  • Verified 3D workflows

Example prompts

  • “drop in a file and draw it”
  • “/editaplot”

Requirements

  • Python 3

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. Reject unsupported platforms before installing anything. Support the CLI/dependency layer only
  2. Locate editaplot.cmd in the installed Skill directory; when working from a cloned repository,
  3. Require the complete repository for first installation. Run repository-root
  4. Reuse an existing compatible Python. If none exists, explain in Chinese that installing Python
  5. Run editaplot.cmd doctor for each new workflow. Allow doctor --repair only for the reported
  6. Run editaplot.cmd start for a new table. Add --intent "" when the
  7. After selecting a candidate template, run `editaplot.cmd understand
  8. Tell a beginner only: what was recognized, the best one to three chart choices, why they fit,
  9. Ask the user to confirm both a one-sentence scientific purpose and the concise element checklist.
  10. If the user supplies a reference figure, first run reference-inspect. Codex may then describe
  11. When color is user-selectable, run editaplot.cmd palettes, show
  12. Internally freeze the confirmed choice with editaplot.cmd plan; never hand-edit a plan or write

What it can do on your machine

Read from SKILL.md and the folder at commit cc12ad4. 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

    Shell commands in SKILL.md call:

    • winget

    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

Editaplot loads about 5.8k tokens when it runs. Until then it costs about 198 tokens; SKILL.md has 2,938 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~198
When it runs · the whole SKILL.md, loaded when a task matches
~5.8k

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 liushunqi8-hash/editaplot2026 at commit cc12ad4, republished under its Apache-2.0 licence (© liushunqi8-hash). 2,938 words, ~5,768 tokens.

Download SKILL.mdSave it as .claude/skills/editaplot/SKILL.md (or your agent's skills folder). This skill also uses 709 other files; get the full folder from GitHub.
name
editaplot
description
Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a callable local Origin/OriginPro installation on physical Windows 10/11 x64. Use for beginner “drop in a file and draw it” requests; XPS, XRD, XAS, PL/TRPL, DSC, NMR, FTIR/IR, UV-Vis, electrochemistry, medical/AI evidence, distribution, relationship, error-bar, bar, stacked, pie, Sankey, radar, heatmap, or verified 3D workflows; project-local Python setup; palette selection; and OPJU/PNG/PDF/TIF verification. Do not use on macOS, Linux, WSL, Wine/CrossOver, Parallels, or other VMs; to install or modify Origin; to redistribute reference images; or to claim an unverified Origin route.

EditaPlot

Turn a scientific question and a read-only table into an auditable, editable Origin figure. Keep the beginner experience conversational; use the deterministic engine for inspection, planning, rendering, exporting, and readback.

Request only scoped Windows permissions

  • Read the complete repository, selected table, and optional local reference image.
  • Write only to the EditaPlot repository, the current user's Codex Skill directory, and the selected source file's parent folder for source-adjacent deliverables.
  • Run the local launcher, PowerShell/Python subprocesses, and an EditaPlot-owned Origin instance in the same active interactive Windows user session.
  • A normal Codex command may first run under an isolated account. If the Origin worker returns origin_codex_sandbox_context, submit a formal, narrowly scoped local-execution request for that exact origin-smoke or render command. Rerun it only if that exact request is approved, either by the user when prompted or by the configured Codex auto-reviewer. Approval is not guaranteed, and this handoff is not a sandbox bypass. Never ask the user to copy the command into a separate PowerShell window or broaden the request to administrator or system-configuration access.
  • Use network access only for repository download/update and locked dependency retrieval. Treat a user-scope winget Python installation as a separate system change that still requires explicit consent.
  • Do not request administrator rights, mouse control, whole-drive write access, cloud upload of private inputs, or DCOM, registry, firewall, user-group, or Origin-installation changes. When Controlled Folder Access, an organization policy, cloud sync, or a read-only location blocks writes, request access only to the affected folder or ask for an explicit alternate output folder.

Start with the beginner path

  1. Reject unsupported platforms before installing anything. Support the CLI/dependency layer only on physical Windows 10/11 x64 with 64-bit CPython 3.10–3.12. Target Origin/OriginPro 2021 and later through external originpro; Origin 2020b and earlier are unsupported by this route. The fully verified live baseline is CPython 3.10 + Origin 2024b / 10.15. Treat another 2021+ version as capability-gated, not automatically verified, until its smoke and complete artifacts pass. State plainly that macOS (Intel/Apple Silicon), Linux, WSL, Wine/CrossOver, Parallels, and other VMs are unsupported in V1. doctor cannot reliably detect every VM, so ask the user to confirm a physical Windows host when that fact is unknown.
  2. Locate editaplot.cmd in the installed Skill directory; when working from a cloned repository, use the repository-root editaplot.cmd. Use an absolute launcher path in commands. Do not make beginners select a Python executable or invoke scripts/editaplot.py directly.
  3. Require the complete repository for first installation. Run repository-root editaplot.cmd setup; never instruct users to copy only skill/editaplot, because that omits the runtime. Read references/runtime.md for setup, discovery, and command details.
  4. Reuse an existing compatible Python. If none exists, explain in Chinese that installing Python is a system-level change. Run winget show first and explain the exact publisher, source, and agreements. Only explicit user confirmation permits a later non-interactive installation of Python.Python.3.12 with user scope and x64 architecture. If winget is unavailable, provide the official python.org Windows installation instructions and wait for the user; never use an untrusted mirror or silently install Python.
  5. Run editaplot.cmd doctor for each new workflow. Allow doctor --repair only for the reported project-local Python dependency repair. Keep all Python packages in .editaplot-venv. Treat Origin as a locally installed user-managed application; never install or modify it during repair.
  6. Run editaplot.cmd start <data-file> for a new table. Add --intent "<user intent>" when the user states a goal. Treat its inspection and recommendation payload as internal working state. Use the original local source path exposed by the attachment. If the host provides only a temporary copied attachment and the original folder cannot be recovered, ask once for the intended local source/output folder before rendering; never guess an unrelated workspace destination.
  7. After selecting a candidate template, run editaplot.cmd understand <data-file> --template-id <id> with the same confirmed mapping that will be used for planning. Group its result into a short checklist: data type; columns to draw; columns used only for support or validation; columns retained but not drawn; proposed figure elements; and calculations that will not be performed. Every source column must appear exactly once. If any item is uncertain, ask for a corrected mapping and run understand again; do not confirm or plan it.
  8. Tell a beginner only: what was recognized, the best one to three chart choices, why they fit, and the smallest scientific decision still required. Do not dump an inspect → recommend → understand → plan pipeline or raw JSON unless they ask for technical detail.
  9. Ask the user to confirm both a one-sentence scientific purpose and the concise element checklist. Freeze the exact proposal_hash, approved derived-item IDs, and resolved ambiguity choices in --semantic-confirmation-json. Never reuse a confirmation after the source, mapping, purpose, or proposal hash changes. When confidence is low, candidate margins are small, roles or units are ambiguous, or a display transformation is proposed, ask only the additional focused questions needed.
  10. If the user supplies a reference figure, first run reference-inspect. Codex may then describe only its panel/mark/encoding/layout/style grammar in the strict ReferenceFigureSpec JSON and run reference-review; the runtime performs no OCR or model inference. Show the adopted and rejected features, bind every essential mark to confirmed renderable user data, and obtain a separate hash-bound confirmation. Never copy reference values, labels, fits, phase assignments, author text, logos, watermarks, or the bitmap into the Origin project. Prefer verified template_adaptation; keep controlled_composition blocked until that exact composition has passed the full Origin evidence gate. A reference cannot add missing evidence or change the confirmed scientific element list. Treat style inferred from the reference as a suggestion, not as the user's instruction. Ask the user to choose one of three modes: keep the verified template default; use a confirmed, allow-listed approximation suggested by the reference; or provide exact custom values. For the exact mode, ask separately for colors, physical line width, fill transparency, page size, and legend visibility, frame, or position. An explicit user choice has precedence over a conflicting reference token. Freeze each reference suggestion as applied, retained_template_default, or rejected; never claim a request was applied unless the selected template has the same verified preview/Origin route and the required Origin object readback.
  11. When color is user-selectable, run editaplot.cmd palettes, show assets/palettes/palette-selector-public.zh-CN.png, and recommend no more than two compatible palette_id values. Read references/palettes.md before freezing one.
  12. Internally freeze the confirmed choice with editaplot.cmd plan; never hand-edit a plan or write a decision back to the source file. For an exact XPS request, write the confirmed values to a separate JSON object and pass its path with --visual-style-json. The supported exact fields are series_colors, line_width_pt, fill_transparency_percent, page_size_cm, legend_visible, legend_position, and legend_frame. Invalid explicit fields or values must fail fast and be corrected with the user; never silently discard them or fall back to a reference/default style. The render command copies this approved plan into the final output folder as render-plan.json.
  13. Treat Origin readiness as technical state only. Doctor performs read-only discovery of Origin.Application, Origin.ApplicationSI, installed candidates, Python, originpro, and OriginExt; it never launches Origin and ready_for_render never means a live connection succeeded. If the default launch registration is present, proceed to the real pre-render smoke without asking the user to open Origin or confirm it again. Keep beginner output to one to three plain-language sentences; leave CLSIDs, registry views, candidates, and stages in JSON. Read the redacted origin_execution_context separately from ready_for_render. A codex_sandbox status requires the exact-command approval handoff above before COM is called; only an approved request may be rerun. Auto-review evaluates that individual request and does not pre-grant Origin access. An unknown Windows execution context is fail-closed and is not an approval request: stop before COM and report that the current Windows identity could not be verified.
  14. Run editaplot.cmd origin-smoke --output-dir <unique-smoke-directory> with launch_isolated: start and own a dedicated Origin instance, perform the live smoke and version handshake, then apply the template capability decision. This command is mandatory after planning and before formal rendering. attach_existing is an explicit advanced mode only; never reset, overwrite, or close a user-owned project, and detach instead of exiting. Report failures by technical stage and next step without speculation. Never use mouse automation or provide application patches or bypass instructions. The runtime must attempt to clean a partial EditaPlot-owned activation and may try one fresh isolated instance for a retryable startup code only if cleanup succeeds. Cleanup failure returns origin_activation_cleanup_failed and stops. It must then wait with sec -poc 30 and confirm run.isOCready() before reading the version or creating a project. Never loop, switch to ApplicationSI, edit DCOM/registry permissions, or tell a beginner to run the whole workflow as administrator. After the automatic attempt is exhausted, request approval for at most one retry in the same active Windows-user context and use a fresh empty sibling smoke directory so the first report remains intact. origin_com_class_not_registered and origin_com_activation_access_denied stop without automatic retry. Do not force-terminate a Python worker merely because it has run for a long time: it may own a hidden Origin instance. Preserve diagnostics and report the last progress stage before proposing any user-controlled cancellation. Keep the sandbox approval handoff distinct from an activation retry: the former happens before COM, while the latter is available only after the bounded activation/cleanup policy has run. When primary activation and cleanup both fail, expose only primary_activation_code, primary_activation_stage, cleanup_error_code, and cleanup_error_stage. Never include a Windows account name, local path, raw HRESULT, or raw COM text in that structured diagnostic payload, and never retry because both pairs are present. Current EditaPlot workers serialize only their active origin-smoke / render Origin section within one signed-in Windows session; data inspection, recommendation, and planning may remain concurrent. Respect origin_job_queue progress, which is emitted immediately when waiting and then about every 30 seconds. Ordering is not guaranteed to be strict FIFO. The 30-minute limit applies only to the waiting job: it stops that waiter without killing or interrupting the active holder. Do not submit a duplicate while a queue message is visible. Manual scripts, older EditaPlot releases, and unrelated programs are outside this coordination boundary.
  15. Only after that smoke passes, render an allowed template route with editaplot.cmd render <plan>. Keep an EditaPlot-owned Origin instance open after success unless the user requests otherwise. By default, let the runtime create a direct sibling of the source file named <source_stem>_EditaPlot_YYYYMMDD_HHMMSS; keep all formal artifacts in that folder. Do not redirect ordinary runs to the repository, Skill directory, current working directory, or a shared global output folder. Use --output-dir only when the user explicitly requests another location.
  16. Run editaplot.cmd verify <output-directory> against that source-adjacent folder and perform human visual QA. If smoke or render fails, a Python preview or standalone PNG/PDF/SVG is only a preview and must not be presented as completed Origin work. Formal success requires the editable OPJU, PNG, PDF, TIF, object readback, and human visual QA together.

Before any render, read references/origin-safety.md, references/figure-contract.md, and references/verification.md. For a new table or chart decision, read references/data-contracts.md, references/chart-selection.md, and references/semantic-understanding.md. When a reference image is supplied, also read references/reference-figures.md.

Show full SKILL.md (1,114 more words)Show less

Keep scientific decisions with the user

  • Treat the original data file as immutable. Never overwrite it, fill missing source columns, or invent measurements. Permit helper columns only in memory or the editable Origin project.
  • Classify every source column before planning as primary render, secondary render, support-only, retain-not-render, or uncertain. Support-only and retained columns cannot become visible through a reference image. An unknown numeric column is a question, not another automatic curve.
  • Distinguish scientific analysis from display transformation. Never silently normalize, smooth, fit, remove outliers, calculate error bars, identify phases, or infer material peaks.
  • For GSAS/GSAS-II Rietveld data, distinguish Observed, Calculated, optional Background, supplied Difference, explicit Phase positions, and non-rendering control/diagnostic columns. Preserve an upstream Publication Diff exactly; never apply a second display offset.
  • For XPS, keep cosmetic preferences separate from the scientific contract. A user may explicitly request exact series colors, physical line widths, fill transparency, a safe page/aspect ratio, and legend show/hide, borderless, or position choices. Apply only fields supported and read back by the selected verified XPS renderer; otherwise retain the default or reject the field visibly. Neither a user style request nor a reference image may change source values or column roles, the high-to-low binding-energy axis contract, component identity, residual disposition, or the verified single-region set_fill_area(..., type=9) / -pfm 3 fill implementation.
  • For SHAP, accept only externally precomputed per-sample contributions. Never train a model or invoke SHAP. Mean |SHAP| and optional group percentages may only summarize those supplied rows with the allow-listed formulas recorded in the semantic proposal and explicitly approved; never invent contributions or silently reorder features.
  • When the user requests separate importance bars, a beeswarm and a two-level contribution ring, select shap_dashboard. Require explicit Feature Group, confirm feature/group percentages using one total Mean |SHAP| denominator, and offer blue–white–wine, purple–green–yellow, or red–yellow–blue. Freeze the selection as mapping plot_mode dashboard_blue_red, dashboard_viridis, or dashboard_red_blue; do not substitute a general categorical palette for this continuous scale.
  • Confirm unknown units, error semantics, percentage denominators, meaningful order, dual axes, and any other choice that can change the claim.
  • Recommend from the scientific question and data structure, not aesthetics alone. Refuse a misleading chart even when technically renderable.
  • Keep template route status (verified, experimental, or unsupported) separate from current host compatibility (verified, compatible_unverified, or blocked). Never relabel a compatible_unverified Origin version as verified; continue only when its smoke succeeds and the selected template's required capabilities are available.
  • Reject decorative 3D. Require a scientifically meaningful third axis; keep a new 3D route experimental until Z-axis, camera, OpenGL type, source mapping, four exports, editable OPJU, readback, and visual QA pass.
  • 对于已验证的 density_ridgeline3d,我只接受 2–6 个真实带单位条件的 mixed-wide 六角色表:上游提供同语义同单位的实线/虚线预计算密度,并为每组提供恰好一个 Focal X。 焦点固定为 Z=0 基线 locator;不要计算 KDE、峰值、阈值、交点或焦点。当前主机还必须先通过 实时 smoke 与 OPEN_GL_3D 能力检查,不能只凭模板已验证就跳过主机门禁。
  • Do not send selected files to any additional network service or include them in public artifacts. A file explicitly provided through Codex remains subject to the user's Codex account, organization, and retention policies; do not claim the Skill can override those policies.
  • Before inspecting medical data or reference images, require the user to confirm that the material follows their institution's rules, is deidentified, and has been checked for burned-in text.
  • Treat panel-plan as a deidentification-aware layout and evidence gate, not an OCR, PHI detector, medical image editor, or merged editable Origin project. Preserve every verified subproject.

Apply the publication-informed contract

  • Make every chart defend one explicit conclusion or evidence role.
  • Use a white background, Arial, restrained color families, clear hierarchy, and no rainbow palette, decorative 3D, or unjustified grid.
  • Derive physical Origin dimensions from chart type, data density, series count, and label length. Keep fixed size only for a profile that explicitly requires it, such as legacy fixed C 1s.
  • Convert documented point, line-width, and page-size units correctly. Never copy small journal-page font values directly into Origin API fields; read back the resulting axis and text objects.
  • Keep each condition's color consistent across related panels. Freeze palette IDs and exact HEX values, allowed modes, safe category count, and accessibility constraints into the plan.
  • Let an explicit user style request outrank a style token inferred from a reference image. Color, line-width, transparency, page/aspect, and legend requests are still capability-gated and must be classified as applied, retained default, or rejected before rendering.
  • Do not let a reference image or unverified cosmetic preference silently redefine semantic color mappings for XPS components, signed effects, heatmaps, diagnostic lines, confusion matrices, or similar evidence. An explicit replacement is allowed only through that route's independently verified override with exact series mapping and readback.
  • Give every medical panel one distinct evidence role. Freeze a shared condition-to-color map before composing quantitative panels; require explicit semantic confirmation for a shared legend.
  • Prefer editable labels and Origin objects. A Python preview or embedded bitmap is not an Origin deliverable.
  • Call the result “publication-informed,” never “Nature compliant” or journal-approved.
  • Custom figure title: use a plain text box, do not fight the page-title API. When a user asks for a visible figure title and the verified template does not render one, do not burn time on layer -t or page.title.text$ / page.title.show — on some Origin versions + templates these silently do not appear in the exported figure. Place a text label directly on the layer with layer.add_label(text, x, y) (returns a Label; set font size via set_int('font.size', n)). Coordinates are layer data coordinates:
    • Cartesian: put it just above the axes, e.g. add_label(title, x_min, y_max * 1.05), clear of the legend.
    • Polar: put it just outside the circle on the 90° ray, e.g. add_label(title, 90, r_outer + ~10). If a large offset gets clipped by the page, pull it back to just outside the rim; a slight overlap with the 90° tick is better than a missing title. This is a cosmetic overlay only; it never changes source data, column roles, or the scientific contract. Verify by reading back the exported PNG, not by assuming the API call succeeded.

Report the result in plain language

Return the recognized data shape and roles, selected chart and alternatives, confidence and confirmed transformations, source-adjacent output folder, copied plan, OPJU/PNG/PDF/TIF paths, validation/readback paths, and any remaining human check. For a beginner, translate internal identifiers into natural language, summarize environment state in one to three sentences, and put technical paths after the concise outcome.

Load detailed references only as needed

  • references/runtime.md: launcher, setup, Python discovery, CLI commands, and artifacts.
  • references/chart-selection.md: chart families, ranking rules, and support levels.
  • references/data-contracts.md: accepted layouts, column semantics, and repair guidance.
  • references/semantic-understanding.md: per-column use, element checklist, derived-data lineage, and the hash-bound confirmation gate.
  • references/reference-figures.md: safe reference grammar, bindings, adaptation limits, and separate confirmation.
  • references/figure-contract.md: evidence logic, visual hierarchy, typography, and color rules.
  • references/origin-safety.md: local Automation and verified-API guardrails.
  • references/verification.md: mandatory artifacts, readback, and visual QA.
  • references/showcase.md: neutral demonstration data and gallery policy.
  • references/palettes.md: Chinese palette selector, compatibility, and accessibility limits.

© liushunqi8-hash, Apache-2.0. 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 709 other files (assets) in the repository root of liushunqi8-hash/editaplot2026.

  • SKILL.md
  • .gitattributes
  • .gitignore
  • ASSET_PROVENANCE.md
  • AUTHORS.md
  • CHANGELOG.md
  • CONTRIBUTING.md
  • LICENSE
  • NOTICE
  • PRIVACY.md
  • README.en.md
  • README.md
  • README.zh-TW.md
  • SECURITY.md
  • SUPPORT.md
  • THIRD_PARTY_NOTICES.md
  • assets/gallery/bar-error-groups.png
  • assets/gallery/bubble-indexed-size.png
  • assets/gallery/circular-network.png
  • … and 691 more

Open the folder on GitHubat commit cc12ad4

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Cc Streaming Export Safetydoccker/cc-use-exp1.1k—~2.2kAutomated safety check: PassCustom licence
XLSXnexus-research-lab/nexus151—~501Automated safety check: PassApache-2.0
Create Spreadsheettheexperiencecompany/gaia308—~802Automated safety check: PassCustom licence

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Questions about Editaplot

What does Editaplot do?

Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a…. Editaplot is an agent skill from liushunqi8-hash/editaplot2026. Analyze local scientific CSV, TXT, XLS, or XLSX data; recommend publication-informed charts and Chinese scientific palettes; freeze a reproducible plan; and automate editable figures through a callable local Origin/OriginPro installation on physical Windows 10/11 x64.

When should I use Editaplot?

Editaplot fits situations like: beginner drop in a file and draw it requests; electrochemistry; medical/AI evidence; verified 3D workflows.

How do I install Editaplot in Claude Code?

Run `npx skills add liushunqi8-hash/editaplot2026 --skill editaplot -a claude-code`. Or copy the skill folder (the liushunqi8-hash/editaplot2026 repository) into .claude/skills/editaplot in your project. Claude Code loads it when a task matches its description.

How do I install Editaplot in Codex?

Run `npx skills add liushunqi8-hash/editaplot2026 --skill editaplot -a codex`. Or copy the skill folder (the liushunqi8-hash/editaplot2026 repository) into .agents/skills/editaplot in your project. Codex loads it when a task matches its description.

Can I use Editaplot 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 liushunqi8-hash/editaplot2026 --skill editaplot -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/editaplot, .gemini/skills/editaplot, .github/skills/editaplot and .opencode/skills/editaplot in your project.

What does Editaplot need to run?

Going by SKILL.md and its folder, Editaplot needs the command-line tools its instructions call (winget). Our summary lists: Python 3.

Does Editaplot 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 Editaplot 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 Editaplot use?

Editaplot is published under the Apache-2.0 licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Editaplot use?

About 5.8k tokens (SKILL.md is roughly 23k 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 Editaplot?

Skills that share tags, products or a category with Editaplot: XLSX (rvdbreemen/OTGW-firmware, 207 stars), Markdown Exporter (bowenliang123/markdown-exporter, 272 stars), Cc Streaming Export Safety (doccker/cc-use-exp, 1.1k stars) and XLSX (nexus-research-lab/nexus, 151 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Editaplot?

liushunqi8-hash (a GitHub user) maintains it in liushunqi8-hash/editaplot2026, which has 128 GitHub stars. The repository was last updated on September 20, 2026.

Source: liushunqi8-hash/editaplot2026 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.