Borrowing it
Nothing to install: this file belongs to u9401066/academic-figures-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/u9401066/academic-figures-mcp/main/.codex/skills/academic-figure-drawing-harness/SKILL.mdgit clone --depth 1 https://github.com/u9401066/academic-figures-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/u9401066/academic-figures-mcp/academic-figure-drawing-harness)<a href="https://agentmods.dev/skills/u9401066/academic-figures-mcp/academic-figure-drawing-harness"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/academic-figure-drawing-harness/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/u9401066/academic-figures-mcp/academic-figure-drawing-harness"><img src="https://agentmods.dev/badge/skills/u9401066/academic-figures-mcp/academic-figure-drawing-harness.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00698 |
| Opus 5 | $0.00022 | $0.00349 |
| Sonnet 5 | $0.00009 | $0.00140 |
| Haiku 4.5 | $0.00004 | $0.00070 |
Grade A, and why
academic-figure-drawing-harness scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to academic-figure-drawing-harness — 1 line differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Academic Figures MCP: Codex Drawing Harness
這個技能專為整合 Codex 原生繪圖能力與 MCP 提供的 Gemini 圖像生成、PubMed 學術圖表檢索而設計。
核心策略 (Core Strategies)
-
原生與生成結合 (Hybrid Rendering)
- 結構化與流程圖: 優先使用 Codex 原生的 Markdown mermaid 語法、SVG 或 Python matplotlib/plotly 繪製精確的架構圖、長條圖、散佈圖與數據模型。
- 複雜醫學/生物插圖: 使用 MCP 工具(如 mcp_academic-figu_generate_figure 或 Gemini tools)生成高度複雜的 3D 解剖圖、顯微組織圖、或不規則概念圖。
- 雙重驗證: 如果需要,使用 mcp_academic-figu_plan_figure 來規劃最適切的呈現路由(決定應該用程式繪圖還是 AI 生成)。
-
學術級距要求 (Citation-Ready & Provenance)
- 引用的出處必須準確,可利用 PubMed 工具 unified_search 或 get_article_figures 索取參考來源或範例圖片。
- 生成的文字標題 (Caption) 必須符合學術期刊規範 (包含圖號、簡短標題、詳細說明、與 PMID 出處)。
-
編輯與優化 (Iterative Refinement)
- 當產生初步圖表後,利用互動工具 mcp_academic-figu_evaluate_figure (8 維度品質評估) 或 mcp_academic-figu_edit_figure 根據使用者回饋進行微調 (例如改顏色、調佈局)。
- 原生 SVG/Mermaid 代碼請直接利用 Codex 的 text edit 能力與 replace_string_in_file 重構並更新。
操作流程 (Workflow)
- Step 1: 規劃圖表 (Plan) 取得需求或文獻內容後,分析合適的圖表類型 (figure_type: flowchart, mechanism, comparison, data_visualization 等)。
- Step 2: 選擇路由 (Route Selection)
- 若能用程式化表達 (如統計數據),引導 Codex 撰寫 Python 腳本或 Mermaid。
- 若需精美點陣圖,呼叫 generate_figure。
- Step 3: 附加上下文與組裝 (Assemble)
產生最終圖片的 Markdown 嵌入格式
,並加上完整的學術來源與 PICO/MeSH 背景說明。
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 35 lines · 44 tokens per session scan A 31946190f65b
academic-figure-drawing-harness is a skill published in the GitHub repository u9401066/academic-figures-mcp (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 44 tokens to every session and 698 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to academic-figure-drawing-harness, differing in 1 line, and is treated as a copy.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…