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 analyticalmonk/explain-this --skill explaining-codebasesgit clone --depth 1 https://github.com/analyticalmonk/explain-thisWrote 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/analyticalmonk/explain-this/explaining-codebases)<a href="https://agentmods.dev/skills/analyticalmonk/explain-this/explaining-codebases"><img src="https://agentmods.dev/badge/skills/analyticalmonk/explain-this/explaining-codebases/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/analyticalmonk/explain-this/explaining-codebases"><img src="https://agentmods.dev/badge/skills/analyticalmonk/explain-this/explaining-codebases.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 | $0.00084 | $0.01054 |
| Opus 5.5 | $0.00034 | $0.00422 |
| Sonnet 5.5 | $0.00017 | $0.00211 |
| Haiku 4.5 | $0.00008 | $0.00105 |
Grade A, and why
explaining-codebases 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explaining Codebases
Overview
This skill explains code as it actually exists - a repository, a service, or a set of source files. The output is the same distill-style, single self-contained interactive explainer that creating-explainers produces. What differs is the intake (navigating real code instead of reading a paper) and the figure types (architecture diagrams, data-flow, execution traces, annotated code walkthroughs). It handles both onboarding overviews of a whole codebase and deep-dives on one mechanism.
Required Background
REQUIRED: Use creating-explainers for everything about the output - the HTML template, voice and style, base figure archetypes, color palettes, the outline/scaffold/prose/polish workflow, and the quality checklist. This skill only adds what is specific to code. Do not duplicate that material here.
When to Use
Use when the subject is code:
- Architecture / onboarding overview - how a project is structured: its modules, how data flows between them, the key abstractions, how the pieces fit. For a new contributor who needs the map.
- Single-mechanism deep-dive - how one algorithm, feature, or subsystem works, traced through the real implementation.
The skill picks the angle from the request and confirms it with the user during intake (overview and deep-dive want different figures and different depth).
When NOT to use: a paper, a topic, or any non-code source. Use creating-explainers instead.
Code Intake
See references/code-intake.md. In short: pick the angle, navigate the repository to find entry points and module structure, identify the spine concept (the one path or idea the article tracks), map the architecture, and pull real code snippets anchored to path:line. Quote actual code; never paraphrase code as if quoting it.
Code-Specific Figures
See references/code-figure-archetypes.md for the patterns:
- Architecture / module diagram - modules as boxes, dependencies as arrows
- Data-flow / sequence diagram - an item (request, message, token) moving through stages
- Execution-trace stepper - step through an algorithm with state and the current line highlighted
- Annotated code walkthrough - a code block whose lines reveal annotations as you step or hover
What ships with it
3 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 · 69 lines · 84 tokens per session scan A 6d52de745455
explaining-codebases is a skill published in the GitHub repository analyticalmonk/explain-this (23 stars, last pushed yesterday), licensed MIT. It adds 84 tokens to every session and 1,054 once invoked, about $0.0003 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.
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