Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add joshua-zyy/academic-paper-writer --skill academic-figuregit clone --depth 1 https://github.com/joshua-zyy/academic-paper-writerWrote 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/joshua-zyy/academic-paper-writer/academic-figure)<a href="https://agentmods.dev/skills/joshua-zyy/academic-paper-writer/academic-figure"><img src="https://agentmods.dev/badge/skills/joshua-zyy/academic-paper-writer/academic-figure/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/joshua-zyy/academic-paper-writer/academic-figure"><img src="https://agentmods.dev/badge/skills/joshua-zyy/academic-paper-writer/academic-figure.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 | $0.00235 | $0.00789 |
| Opus 5 | $0.00118 | $0.00394 |
| Sonnet 5 | $0.00047 | $0.00158 |
| Haiku 4.5 | $0.00023 | $0.00079 |
Grade A, and why
academic-figure 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 13d 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.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Academic Figure
CS/AI/ML academic-figure router. 实验数据图默认交付 Python/matplotlib 可编辑 SVG，并执行 CS/AI/ML 图表设计 gate。模型框架图、架构图、overview 图和复杂机制图不属于本 skill 的自动绘制范围；如论文需要此类图，只能输出人工绘制需求、证据清单、caption 草案或 figure blueprint notes。
Router Protocol
- Read
manifest.yaml. It declaresalways_loadfiles,axes, andreferences.on_demand. - Read every file listed under
always_load. These are the skill's binding rules — not reference material. - Apply the loaded material as constraints:
stance.mddefines Python-only plotting, figure contract, visual policy, and scope.red-lines.mddefines absolute prohibitions. Do not negotiate these.output-contract.mddefines deliverables per mode.anti-patterns.mddefines known failure modes and their correct alternatives.
- Select exactly one
modefrom the manifest. If ambiguous, ask one concise clarification only when data source or target use is missing. Requests for model framework, architecture, overview, or mechanism diagrams usefigure-blueprintonly to producemanual_figure_needednotes; never render images, SVG, or prompts. - Echo the selected mode to the user before executing.
- Reach for
references/only when the manifest'sreferences.on_demandcondition is satisfied.
Modes
| Mode | Use when |
|---|---|
chart-from-data |
Data files or numeric results, needs publication plot with CS/AI/ML chart design gate |
figure-blueprint |
Wants figure suggestions for a paper section |
figure-audit |
Existing figure reviewed for publication readiness |
figure-revision |
Existing figure needs revision |
Agent Dispatch
agents/figure_agent.md is dispatched by the orchestrator at Step 6.4. The agent returns figure artifacts, scripts, SVG paths, and reports; it must not independently edit project source code or experimental data.
Completion Criteria
chart-from-data: Figure Contract, CS/AI/ML chart design gate, Python script, source data, editable SVG, QA report — all pass.figure-audit: Every QA item has pass/fail status and concrete remediation.figure-blueprint: Every suggested figure maps to a paper claim and data/evidence source.figure-revision: Revised artifact or instructions, QA report, unchanged evidence traceability.
What ships with it
16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- agents/figure_agent.md 7.5 KB
- manifest.yaml 2.2 KB
- references/api.md 10 KB
- references/chart-types.md 4.7 KB
- references/cs-ai-chart-design-patterns.md 4.7 KB
- references/design-theory.md 4.6 KB
- references/figure-contract.md 2.1 KB
- references/qa-contract.md 1.7 KB
- references/tutorials.md 4.6 KB
- references/workflow-chart-from-data.md 5.6 KB
- scripts/chart_template.py 8.8 KB runs code
- scripts/qa_figure.py 5.8 KB runs code
- static/core/anti-patterns.md 897 B
- static/core/output-contract.md 854 B
- static/core/red-lines.md 941 B
- static/core/stance.md 3.7 KB
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.
- 13d ago First seen · 42 lines · 235 tokens per session scan A c27d4257fbca
academic-figure is a skill published in the GitHub repository joshua-zyy/academic-paper-writer (110 stars, last pushed 2mo ago), licensed MIT. It adds 235 tokens to every session and 789 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
anti-defensive-writing-en
Stops defensive writing across the entire paper lifecycle — writing, revising, cutting, and organizing experiments. Treats the paper as a press conference, not a project summary, lab log, or self-audit: identify the single most publishable strength of the work and build the most favorable, complete, and persuasive…
anti-defensive-writing
A Chinese-language writing guide for presenting a research paper around its strongest supported contribution. It treats the paper as a focused academic presentation rather than a project diary or complete lab record.
light-paper-writing
A research-paper writing workflow that links each important claim to evidence and checks whether the wording matches the strength of that evidence.
light-result-analysis
A research-results review workflow that explains what experiment results may mean and how strongly they support each claim. It uses statistical checks such as effect sizes, confidence intervals, and corrections for testing many hypotheses.
light-figure
A research-figure workflow for planning and creating publication-ready charts and diagrams. It connects each figure to a paper claim and checks that the visual presentation does not misrepresent the data.
light-research-plan
A research-planning guide for turning an approved idea into a reproducible experiment plan. It defines what to compare, what to measure, when to stop, and how to record seeds, environments, versions, and data splits.