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 OKHP3/skillz --skill doc-and-modernizegit clone --depth 1 https://github.com/OKHP3/skillzWrote 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/okhp3/skillz/doc-and-modernize)<a href="https://agentmods.dev/skills/okhp3/skillz/doc-and-modernize"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/doc-and-modernize/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/okhp3/skillz/doc-and-modernize"><img src="https://agentmods.dev/badge/skills/okhp3/skillz/doc-and-modernize.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 | $0.00208 | $0.11574 |
| Opus 5.5 | $0.00083 | $0.04630 |
| Sonnet 5.5 | $0.00042 | $0.02315 |
| Haiku 4.5 | $0.00021 | $0.01157 |
Grade A, and why
doc-and-modernize 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 — 851 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Documentation & Modernization
Two complementary workflows for a repository the user already has checked out locally, bundled as one skill:
- Documentation mode — produce one definitive, cited architecture document from the code on disk. Ideal for onboarding, system-design maps, or as the evidence base for a modernization effort.
- Modernization mode — turn that architecture into a phased, safety-laddered plan to upgrade, migrate, or rewrite a legacy system.
Mode selection
- If the user wants to understand, document, map, research, or onboard onto a codebase, run Documentation mode.
- If the user wants to modernize, migrate, upgrade, or rewrite a system, run Modernization mode. Modernization mode is self-sufficient: if no architecture document exists yet, it runs the Documentation mode workflow first (in the same pass), then continues straight through to the plan.
When in doubt, produce the architecture document first — it is the audited evidence base both modes rely on.
Documentation mode
Generate one definitive, cited architecture document for a repository the user already has checked out locally. The goal is a writeup someone could hand to a new engineer as their onboarding reference — broad enough to cover the whole system, deep enough on the hard parts to be useful, and trustworthy because every claim traces back to a file on disk.
Why local-first
Reading from the local checkout (not the GitHub API or the web) is the deliberate
default. It is faster, free, avoids rate limits, and — most importantly — it
describes the exact code in front of you rather than whatever main happens
to look like remotely. The one tradeoff is that remote-only facts (star counts,
full CI run history, sibling repos) aren't visible. That's fine: state those as
out-of-scope or mark them [UNVERIFIED] rather than guessing.
Local-first is not local-never-remote: a web/API lookup is a deliberate
last-resort fallback, reserved for a fact that genuinely cannot be determined
from disk and that materially matters to the document. When you do reach for it,
flag the result clearly (e.g. [UNVERIFIED] / sourced-remotely) so the reader
knows it didn't come from the checkout, and never let it become the easy path
that displaces reading the code on disk.
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.
- 1mo ago First seen · 851 lines · 208 tokens per session scan A a1b5ff3752fa
doc-and-modernize is a skill published in the GitHub repository OKHP3/skillz (3 stars, last pushed today), licensed MIT. It adds 208 tokens to every session and 11,574 once invoked, about $0.0008 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 2026-09-03.
Other skills, from other repositories
vastai-sdk
Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing.
pm-agile
A workflow for setting up an agile development process, where work is delivered in repeated short cycles and reviewed regularly.
pm-portfolio
A product-portfolio planning workflow for comparing several products and deciding where each fits in its market and lifecycle.
pm-interview
A user-interview and research planning workflow, with instructions in Chinese, for defining goals, participants, interview questions, and analysis methods.
diagram-design
Create branded architecture, architecture delta, IT current-state, flowchart, sequence, state machine, ER/data model, timeline, swimlane, quadrant, radar/spider, polar chart (polar/radial lollipop), loop/flywheel, nested, tree, org chart, layer stack, exploded axonometric, axonometric plan, Venn, pyramid/funnel…
intelligent-content-system
A content workflow tool that gathers web content, creates supporting images and social posts, and publishes them across WeChat, Xiaohongshu, X, and Bilibili. Xiaohongshu is a Chinese social platform, while Bilibili is a Chinese video platform.