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 alinaqi/maggy --skill basegit clone --depth 1 https://github.com/alinaqi/maggyWrote 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/alinaqi/maggy/base)<a href="https://agentmods.dev/skills/alinaqi/maggy/base"><img src="https://agentmods.dev/badge/skills/alinaqi/maggy/base/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/alinaqi/maggy/base"><img src="https://agentmods.dev/badge/skills/alinaqi/maggy/base.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 412 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00014 | $0.04612 |
| Opus 5.5 | $0.00006 | $0.01845 |
| Sonnet 5.5 | $0.00003 | $0.00922 |
| Haiku 4.5 | $0.00001 | $0.00461 |
Grade A, and why
base 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 1mo 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 — 537 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Base Skill - Universal Patterns
Core Principle
Complexity is the enemy. Every line of code is a liability. The goal is software simple enough that any engineer (or AI) can understand the entire system in one session.
Simplicity Rules
These limits apply to every file created or modified.
Function Level
- Maximum 20 lines per function - if longer, decompose IMMEDIATELY
- Maximum 3 parameters per function - if more, use an options object or decompose
- Maximum 2 levels of nesting - flatten with early returns or extract functions
- Single responsibility - each function does exactly one thing
- Descriptive names over comments - if you need a comment to explain what, rename it
File Level
- Maximum 200 lines per file - if longer, split by responsibility BEFORE continuing
- Maximum 10 functions per file - keeps cognitive load manageable
- One export focus per file - a file should have one primary purpose
Module Level
- Maximum 3 levels of directory nesting - flat is better than nested
- Clear boundaries - each module has a single public interface
- No circular dependencies - ever
Enforcement Protocol
Before completing ANY file:
- Count total lines - if > 200, STOP and split
- Count functions - if > 10, STOP and split
- Check each function length - if any > 20 lines, STOP and decompose
- Check parameter counts - if any > 3, STOP and refactor
If limits are exceeded during development:
⚠️ FILE SIZE VIOLATION DETECTED
[filename] has [X] lines (limit: 200)
Splitting into:
- [filename-a].ts - [responsibility A]
- [filename-b].ts - [responsibility B]
Never defer refactoring. Fix violations immediately, not "later".
Architectural Patterns
Functional Core, Imperative Shell
- Pure functions for business logic - no side effects, deterministic
- Side effects only at boundaries - API calls, database, file system at edges
- Data in, data out - functions transform data, they don't mutate state
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.
- 1mo ago Changed · +1 lines db198378a531
- 1mo ago Changed · +2 lines cd8ed5493ee0
- 1mo ago First seen · 534 lines · 14 tokens per session scan A 5d8a2db21750
base is a skill published in the GitHub repository alinaqi/maggy (711 stars, last pushed 9d ago), licensed MIT. It adds 14 tokens to every session and 4,612 once invoked, about $0.0001 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.
Other skills, from other repositories
browser-use
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers hosted cloud browsers for AI agents: the browser-use Python library (Browser(usecloud=True)), Playwright, Puppeteer or any CDP client.
benchmark-workflow
Run, diagnose, or change Xberg extraction benchmarks, quality scoring, benchmark fixtures, artifact contracts, and independently sourced ground truth. Load for the Benchmarks workflow or benchmark-harness work, not ordinary unit tests.
python
Use when the task is Python itself, in any framework or none: PEP 695 generics, mypy --strict typing, dataclass/Protocol/TypedDict/Enum choices, asyncio.TaskGroup, stdlib idioms, src/ layout + pyproject.toml with uv, ruff+mypy+pytest gate. NOT a FastAPI/ASGI service (that is fastapi), NOT a deep pytest suite (that is…
python-testing
A Python testing guide covering pytest, test coverage, and test-driven development (TDD), a method of writing a failing test before the code that makes it pass.
python-idioms
Modern Python (3.11+) idioms: type annotations, typing Protocols, Pydantic models, asyncio, pytest fixtures, and Ruff/Mypy strict compliance. Use when writing, refactoring, or reviewing Python applications, APIs, or scripts.
long-running-work
Carrying complex coding and project work through commands that take minutes or hours: evals, benchmarks, full builds and test suites, migrations, servers, multi-round runs. Use when a command may run past a few minutes, timed out once, or when the task spans several rounds of run, read results, fix, run again.