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 alivirgo/Major-AI-Skills --skill ast-skeletonizergit clone --depth 1 https://github.com/alivirgo/Major-AI-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/alivirgo/major-ai-skills/ast-skeletonizer)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/ast-skeletonizer"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/ast-skeletonizer/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/alivirgo/major-ai-skills/ast-skeletonizer"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/ast-skeletonizer.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 | $0.00025 | $0.01259 |
| Opus 5 | $0.00013 | $0.00629 |
| Sonnet 5 | $0.00005 | $0.00252 |
| Haiku 4.5 | $0.00003 | $0.00126 |
Grade A, and why
ast-skeletonizer 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 yesterday.
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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AST Code Skeletonization (Signature-Only Context Ingestion)
Overview
When an autonomous coding assistant needs to understand a repository's architecture, dependencies, or available APIs, ingesting full implementation files burns tens of thousands of tokens on internal loops, private variable assignments, and boilerplate logic.
The AST Code Skeletonization Protocol parses source code into an Abstract Syntax Tree and strips all function and method bodies - retaining only imports, type definitions, interface contracts, class signatures, and exported method headers.
This generates an ultra-high-density structural map that reduces context token consumption by 80% to 90% while preserving 100% of the API surface.
Full File vs. Skeletonized Signature Map
┌─────────────────────────────────────────────────────────────┐
│ AST Skeletonization Mapping │
│ │
│ Full Implementation Ingestion (520 Tokens): │
│ export class PaymentGateway { │
│ private apiKey: string; │
│ constructor(config: GatewayConfig) { │
│ this.apiKey = config.apiKey; │
│ this.validateKey(this.apiKey); │
│ // 40 lines of internal setup & logging logic... │
│ } │
│ async processCharge(req: ChargeRequest): Promise<Result> │
│ const payload = { amount: req.amount, cur: req.cur }; │
│ // 30 lines of HTTP retries, exponential backoffs... │
│ return parseResponse(await fetch(...)); │
│ } │
│ } │
│ │
│ AST Skeletonized Signature (65 Tokens - 87.5% Reduction): │
│ export class PaymentGateway { │
│ constructor(config: GatewayConfig); │
│ async processCharge(req: ChargeRequest): Promise<Result>;│
│ } │
└─────────────────────────────────────────────────────────────┘
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.
- yesterday Changed · -13 tokens per session 6a8a1a5619f8
- 7d ago First seen · 145 lines · 38 tokens per session scan A 8da27eb4ee5d
ast-skeletonizer is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,259 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 2026-09-05.
Other skills, from other repositories
agent-v3-memory-specialist
Agent skill for v3-memory-specialist - invoke with $agent-v3-memory-specialist.
mem0-tour
Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
mem0-cli
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0…
mem0-remember
Stores a memory verbatim from user input with appropriate type classification and metadata. Use when the user says remember this, save this, store this, note that, or explicitly asks to record a decision, preference, convention, or learning.
status
Show whether Mem0 memory is working in this repository, covering configuration, capture state, pending flushes, and whether the Mem0 API key is valid. Use when the user asks whether memory is on, why a memory is missing, or anything looks broken.
pause
Pause Mem0 memory capture on this machine. Use when the user wants to stop memories being recorded, for example for private work or experiments.