Borrowing it
Nothing to install: this file belongs to zhnnky329/MathModeling-skills. 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/zhnnky329/MathModeling-skills/main/.claude/skills/figure-table-planner/SKILL.mdgit clone --depth 1 https://github.com/zhnnky329/MathModeling-skillsWrote 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/zhnnky329/mathmodeling-skills/figure-table-planner)<a href="https://agentmods.dev/skills/zhnnky329/mathmodeling-skills/figure-table-planner"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/figure-table-planner/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/zhnnky329/mathmodeling-skills/figure-table-planner"><img src="https://agentmods.dev/badge/skills/zhnnky329/mathmodeling-skills/figure-table-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.00515 |
| Opus 5 | $0.00016 | $0.00258 |
| Sonnet 5 | $0.00006 | $0.00103 |
| Haiku 4.5 | $0.00003 | $0.00052 |
Grade A, and why
figure-table-planner 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 11d 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 — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Make every visual evidence-bearing. Prefer fewer useful visuals over a decorative inventory.
Inputs
- method card and decision ledger;
- run summaries and final result analysis;
- robustness evidence;
- solution package and frozen numbers in submission mode;
- existing figures/tables.
Figure Types
- Type 1 diagnostic: internal debugging; never in the paper.
- Type 2 comparison: main vs usable baseline or a genuinely tested alternative; optional in paper.
- Type 3 paper: directly supports a main claim; required only when the claim benefits materially from a visual.
- Type 4 appendix: supplementary evidence referenced from the main text.
Workflow
- List verified claims that need visual or exact tabular support.
- Reuse an existing artifact when it already communicates the claim.
- For each proposed visual record:
- ID and Qx;
- type;
- source artifact and frozen claim IDs when applicable;
- one core claim;
- chart/table form;
- target section;
- status and render needs.
- Ask the human to confirm judgment-bearing Type 3 claims through one compact choice card when they are not already in the decision ledger.
- Save
methods/Qx/qx_figure_table_plan.mdonly when durable planning is needed. In lean exploration, a compact in-conversation plan is sufficient.
Planning Heuristics
- Use tables for exact values, parameters, and small comparisons.
- Use plots for trends, distributions, sensitivity, or many-item comparisons.
- Use diagrams for mechanisms, dependencies, and workflows.
- A main-vs-baseline figure needs compatible metrics and the same evaluation setup.
- Do not create a multi-method comparison merely to imply breadth.
Rules
- Type 1 never enters the paper.
- Type 3 uses final validated sources and a human-confirmed core claim.
- Do not use unresolved exploratory figures as paper evidence.
- Do not fabricate data, captions, or claims.
- Do not fill plans with placeholder sentinels; pause for one human choice instead.
- Every visual must have a source and purpose.
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.
- 11d ago First seen · 63 lines · 32 tokens per session scan A ea1dead8d5d4
figure-table-planner is a skill published in the GitHub repository zhnnky329/MathModeling-skills (847 stars, last pushed 17d ago), licensed MIT. It adds 32 tokens to every session and 515 once invoked, about $0.0002 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
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…