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/build-context/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/build-context)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/build-context"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/build-context/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/build-context"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/build-context.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 | $0.00023 | $0.01528 |
| Opus 5 | $0.00012 | $0.00764 |
| Sonnet 5 | $0.00005 | $0.00306 |
| Haiku 4.5 | $0.00002 | $0.00153 |
Grade A, and why
build-context 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.
How it starts
The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build Context Skill
Generate a structured guidance/paper-context.md file that captures everything Claude needs to know about a paper before writing, editing, or auditing it. This file is consumed by /audit-section, /check-consistency, /edit-section, /full-paper-audit, /audit-captions, and other writing skills.
Examples
/build-context main.tex-- build context from the paper's LaTeX source/build-context draft.pdf-- build context from a PDF of the paper/build-context notes.md main.tex-- combine author notes with LaTeX source/build-context related_paper.pdf-- extract context from a related paper for reference/build-context-- scan for main.tex or .pdf files in the current project and ask which to use
Input
One or more file paths. Supported formats:
.tex-- LaTeX source (richest; extracts section structure, labels, equations, citations).pdf-- PDF file (read with the Read tool; extracts prose content and structure).md-- Markdown notes (author's own description of the paper, key results, terminology)
If no arguments are provided, scan the current project directory for main.tex or *.pdf files and prompt the user to select.
Workflow
Step 1: Read Source Files
- Read each provided file
- For
.tex: extract the full document - For
.pdf: read the PDF (use pages parameter for large files; start with first 10 pages, then continue if needed) - For
.md: read as-is (these are usually the author's own notes)
Step 2: Extract Paper Identity
From the source material, identify:
- Title: from
\title{}or document header - Authors: from
\author{}or byline - Abstract: from
\begin{abstract}or first section - Core contribution: 1-3 sentences summarizing what the paper does that is new
Step 3: Extract Key Results
Identify the paper's main quantitative and qualitative findings:
- Primary results: the headline findings (with specific numbers if available)
- Secondary results: supporting findings
- Robustness: what robustness checks are performed
- Null results: any important non-findings
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 · 184 lines · 23 tokens per session scan A 1e7c07600820
build-context is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 23 tokens to every session and 1,528 once invoked, about $0.0001 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.
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