Borrowing it
Nothing to install: this file belongs to Alexander-M-Dickerson/ai-asset-pricing. 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/Alexander-M-Dickerson/ai-asset-pricing/main/.claude/skills/publication-figures/SKILL.mdgit clone --depth 1 https://github.com/Alexander-M-Dickerson/ai-asset-pricingWrote 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/alexander-m-dickerson/ai-asset-pricing/publication-figures)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/publication-figures"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/publication-figures/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/alexander-m-dickerson/ai-asset-pricing/publication-figures"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/publication-figures.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 | $0.00056 | $0.02398 |
| Opus 5.5 | $0.00022 | $0.00959 |
| Sonnet 5.5 | $0.00011 | $0.00480 |
| Haiku 4.5 | $0.00006 | $0.00240 |
Grade A, and why
publication-figures 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 2mo 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Publication-Ready Figures
For this repo, the production plotting toolkit is fintools.figures. Read
docs/ai/figures.md first, then choose the plotting path deliberately:
- Use native
fintools.figureshelpers for repo work, Word proof packs, validation checks, and dataframe-to-figure suites. - Use
style="fins"for the house publication style andstyle="ft"for FT-style output. - Use the legacy skill-local
finance.mplstyle/figutils.pyassets only when the user explicitly wants the older standalone helper style or needs a portable snippet outside the package workflow.
To recreate the FT validation gallery:
python tools/figure_examples.py --style ft --docx --output results/figures
To recreate the house-style gallery:
python tools/figure_examples.py --style fins --docx --output results/figures
Generated PNG/PDF/DOCX/caption files belong under ignored results/figures/
paths. Do not commit maintainer proof packs or local gallery outputs.
Apply these conventions whenever creating figures. The goal: every figure Claude produces is publication-ready by default — no manual cleanup needed.
Legacy Helper Quick Start
Prefer fintools.figures for this repo. The helper assets below remain
available for standalone or explicitly requested legacy publication-style
plots.
Copy finance.mplstyle from this skill directory into the project, then:
import matplotlib.pyplot as plt
plt.style.use('path/to/finance.mplstyle')
Or apply inline (no file needed):
import matplotlib.pyplot as plt
plt.rcParams.update({
'font.family': 'serif',
'font.serif': ['Times New Roman', 'STIXGeneral', 'DejaVu Serif'],
'mathtext.fontset': 'stix',
'font.size': 9,
'axes.labelsize': 9,
'xtick.labelsize': 8,
'ytick.labelsize': 8,
'legend.fontsize': 8,
'axes.linewidth': 0.6,
'axes.spines.top': False,
'axes.spines.right': False,
'lines.linewidth': 1.2,
'xtick.direction': 'out',
'ytick.direction': 'out',
'legend.frameon': False,
'figure.dpi': 150,
'savefig.dpi': 600,
'savefig.format': 'pdf',
'pdf.fonttype': 42,
})
What ships with it
2 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.
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.
- 2mo ago First seen · 228 lines · 56 tokens per session scan A eddfae7f39a1
publication-figures is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 6mo ago), licensed MIT. It adds 56 tokens to every session and 2,398 once invoked, about $0.0002 per session on Opus 5.5. 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.
publication-figures compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| publication-figuresAlexander-M-Dickerson/ai-asset-pricing | Skill | 59 | 6mo ago | MIT | A | 56 | Claude Code |
| instrument-data-to-allotropeanthropics/knowledge-work-plugins | Skill | 35k | 2d ago | Apache-2.0 | A | 123 | Claude Code |
| exploratory-data-analysisK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 83 | Claude Code |
| matlabK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 44 | Claude Code |
| phylogeneticsK-Dense-AI/scientific-agent-skills | Skill | 56k | 4d ago | MIT | A | 71 | Claude Code, Codex |
| research-engineerdavila7/claude-code-templates | Skill | 33k | yesterday | MIT | A | 43 | Claude Code, Codex |
| mapping-to-snomedmaziyarpanahi/openmed | Skill | 5.8k | yesterday | Apache-2.0 | A | 205 | Claude Code |