explain

A command for explaining how a specified part of code works.

In plain words
What is it for?
It is for explaining the behaviour or implementation of a selected section of a program.
Why use it?
It helps clarify unfamiliar code without requiring the reader to work it out alone.

Command for Claude Code

Install

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.

agentmods
npx agentmods add commands/alexeykrol/claude-code-starter/explain
Clone the repo
git clone --depth 1 https://github.com/alexeykrol/claude-code-starter

Made for: Claude Code.

Per session 10 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 874 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00010 $0.00874
Opus 5 $0.00005 $0.00437
Sonnet 5 $0.00002 $0.00175
Haiku 4.5 $0.00001 $0.00087

Measured 3d ago against content hash 726f5cbad423, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

explain 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 3d 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.

archive/v4-working-tree/.claude/commands/explain.md · 148 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

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.

  1. 3d ago First seen · 148 lines · 10 tokens per session scan A 726f5cbad423

Subscribe to this mod's changes

explain is a command published in the GitHub repository alexeykrol/claude-code-starter (192 stars, last pushed 1mo ago), with no licence file. It adds 10 tokens to every session and 874 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.

Related

Other commands, from other repositories

courseware-qa

Audit the WSQ courseware (PPT, LP, LG, labs) and the assessment set (WA + PP/CS) against the published Tertiary Infotech standards at https://tertiarycourses.github.io/wsqcourseware/ — renders every checked page to an image and reports pass/fail.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 64 tokens

gdrive-push

Push this course's courseware (PPT + PDF, Learner Guide, Lesson Plan, assessments) to the user-provided Google Drive courseware folder — archiving superseded versions into archive/ first, never deleting, and emitting anyone-with-link viewer links.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 53 tokens

assessment-gen

Generate the WSQ assessment set for this course — the Written Assessment (WA/SAQ) and the PP or Case Study, each as a question paper and an answer key — mirroring the original paper, then audit with /courseware-qa.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 51 tokens

courseware-gen

Generate the WSQ courseware for this course — the slide deck (PPT), Lesson Plan (LP) and Learner Guide (LG) plus their PDFs — to the published Tertiary Infotech standards, then audit with /courseware-qa.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 52 tokens

wsq-setup

Install or update the WSQ courseware toolchain (skills, commands, the courseware-qa agent, the push scripts and the three hooks) in this project or at user level, from github.com/tertiarycourses/wsqskills. Never overwrites a course-customised generator.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 0 tokens

tms-push

Update the course on lms-tms.tertiaryinfotech.com — set the Trainer Slides / Learner Slides / Learner Guide / Lesson Plan / Activities-Lab URLs from the course's Google Drive folder, and attach the assessment. QUESTION PAPERS ONLY (WA + PP/CS); the answer keys are trainer-only and never reach the LMS.

tertiarycourses/TGS-2020503207-AI-Vibe-Coding-for-Multi-Agents-System · 0 tokens