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/outline/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/outline)<a href="https://agentmods.dev/skills/alexander-m-dickerson/ai-asset-pricing/outline"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/outline/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/outline"><img src="https://agentmods.dev/badge/skills/alexander-m-dickerson/ai-asset-pricing/outline.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 | $0.00019 | $0.00792 |
| Opus 5 | $0.00010 | $0.00396 |
| Sonnet 5 | $0.00004 | $0.00158 |
| Haiku 4.5 | $0.00002 | $0.00079 |
Grade A, and why
outline 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 — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Outline Skill
Review the current paper structure: section balance, word counts, Cochrane-principle compliance, and structural integrity.
Examples
/outline— full structural analysis of main.tex/outline balance— check section length balance only/outline cochrane— Cochrane-principle compliance check only
Workflow
Step 1: Read Current Structure
- Read
main.tex - Extract all
\section{},\subsection{},\subsubsection{}commands - Count lines and estimate words per section (between
%% BEGIN/ENDmarkers) - Verify
%% BEGIN/ENDmarkers are present and match registered keys
Registered section keys: Check the project's CLAUDE.md or guidance/paper-context.md for the section key registry. If neither exists, discover keys by scanning for %% BEGIN: markers in main.tex.
Step 2: Structural Analysis
Section Presence:
- Verify all expected body sections are present (based on registered keys or discovered markers)
- Verify appendices are present if referenced in the body
- Flag any sections that appear in
main.texbut are not in the registered key list
Section Balance:
- Flag sections that are >2x the average body-section length
- Flag sections that are <0.25x the average body-section length
- Introduction target: ~3 pages (Cochrane)
- Conclusion target: ~1--2 paragraphs
Organization (Cochrane Principles):
- Is the main result presented as early as possible?
- Is there anything before the main result that a reader doesn't need?
- Are robustness checks in the appendix (not cluttering the body)?
- Is the literature review AFTER the contribution (not before)?
Step 3: Project-Specific Structural Checks
If guidance/paper-context.md exists, run its registered structural checks. Common checks include:
- Are key figures/tables referenced in the introduction?
- Does the introduction enumerate all main contributions?
- Does the conclusion mention stated deliverables (data, code, packages)?
- Is the paper's terminology used consistently in section headers?
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 · 95 lines · 19 tokens per session scan A 480e5babaa6c
outline is a skill published in the GitHub repository Alexander-M-Dickerson/ai-asset-pricing (59 stars, last pushed 4mo ago), licensed MIT. It adds 19 tokens to every session and 792 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.
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…
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…
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.
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…