sova: Skill for Claude Code

.agents/skills/sova-develop-explain/SKILL.md

sova-develop-explain is a skill for Claude Code, Codex from xsovad06/sova. It costs 23 tokens per session (693 once invoked), scanned A, original, Apache-2.0.

A teaching-focused guide for explaining how to build a feature or fix a problem. It compares possible approaches, explains the technologies involved, and includes examples rather than implementing the change.

In plain words
What is it for?
Use it to learn how a feature could be designed, understand unfamiliar tools, compare implementation strategies, and study example code.
Why use it?
Technical explanations often assume knowledge the reader does not have or present only one solution. This gives learners the background, trade-offs, and reasoning behind different choices.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

This is xsovad06/sova's own configuration. It tells Claude Code and Codex how to work on sova itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything sova configures →

Reuse

Borrowing it

Nothing to install: this file belongs to xsovad06/sova. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/xsovad06/sova/main/.agents/skills/sova-develop-explain/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/xsovad06/sova

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for sova-develop-explain

README.md
[![agentmods](https://agentmods.dev/badge/skills/xsovad06/sova/sova-develop-explain/github.svg)](https://agentmods.dev/skills/xsovad06/sova/sova-develop-explain)
Your own site
<a href="https://agentmods.dev/skills/xsovad06/sova/sova-develop-explain"><img src="https://agentmods.dev/badge/skills/xsovad06/sova/sova-develop-explain/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.

agentmods 80×15 button for sova-develop-explain

Your own site · 80×15
<a href="https://agentmods.dev/skills/xsovad06/sova/sova-develop-explain"><img src="https://agentmods.dev/badge/skills/xsovad06/sova/sova-develop-explain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 693 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original 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 5.1 $0.00023 $0.00693
Opus 5.5 $0.00009 $0.00277
Sonnet 5.5 $0.00005 $0.00139
Haiku 4.5 $0.00002 $0.00069

Measured 16d ago against content hash d21332d90bcc, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

sova-develop-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 16d 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.

.agents/skills/sova-develop-explain/SKILL.md · 109 lines

How it starts

The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Explain how the requested feature/fix could be implemented, with deep learning context and technology explanations.

Instructions

You are a senior developer and educator. Your job is NOT to implement, but to EXPLAIN:

  • What are the possible approaches
  • Why each approach works (or doesn't)
  • How the technologies involved work
  • What the user will learn from each approach

Topic to explain: the arguments provided when this skill is invoked


Your Response Should Include

1. Understanding the Problem

Before explaining solutions, clarify:

  • What exactly needs to be done?
  • What is the current state?
  • What are the constraints?
  • Ask clarifying questions if needed

2. Possible Approaches

For each viable approach, explain:

## Approach N: [Name]

### What
[Brief description of the approach]

### How It Works
[Technical explanation of the mechanism]

### Why This Works
[The underlying principles that make this approach valid]

### Pros
- [Advantage 1]
- [Advantage 2]

### Cons
- [Disadvantage 1]
- [Disadvantage 2]

### When to Use
[Scenarios where this approach is best]

### Code Example
[Minimal example showing the approach]

3. Technology Deep Dives

For each technology involved, provide learning context:

  • What: What it is
  • Why it exists: The problem it solves
  • How it works: Internal mechanics
  • Key concepts: Important things to understand

4. Architecture Patterns Explained

Explain the relevant architectural patterns used in this project:

  • Why the separation of concerns exists
  • What each layer is responsible for
  • How data flows through the layers

5. Common Pitfalls & Why They're Bad

Pitfall Why It's Bad What to Do Instead
Logic in controllers/views Untestable, violates SRP Move to services
N+1 queries Performance disaster Use eager loading
No input validation Security risk Validate at boundaries
Catching generic exceptions Hides bugs Catch specific exceptions

Read the full file on GitHub · 109 lines

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. 16d ago Changed d21332d90bcc
  2. 22d ago First seen · 109 lines · 23 tokens per session scan A c4415888f17b

Subscribe to this mod's changes

sova-develop-explain is a skill published in the GitHub repository xsovad06/sova (2 stars, last pushed today), licensed Apache-2.0. It adds 23 tokens to every session and 693 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 2026-10-08.

Related

Other skills, from other repositories

totem-compiled-rules

Compiled architectural rules and lessons from the Totem knowledge base. Load this when reviewing code for pattern violations or architectural drift.

mmnto-ai/totem · 31 tokens

scaffold-exercises

Create exercise directory structures with sections, problems, solutions, and explainers that pass linting. Use when user wants to scaffold exercises, create exercise stubs, or set up a new course section.

vraj-ai/skills · 45 tokens

teach

Teach the user a new skill or concept, within this workspace.

vraj-ai/skills · 15 tokens

find-simplifications

Use for a periodic repo-wide sweep of qwen-code for accumulated excess surface — dead components and files, orphaned locale keys, exports nothing consumes, added-then-removed scaffolding — filing candidates on a tracking issue and landing only what a maintainer has said yes to. Repo-wide and evidence-first; every…

QwenLM/qwen-code · 103 tokens

swarm-pr-review

Run a graph-guided, tool-augmented PR review using context packing, parallel exploration, mandatory repository-agnostic risk-family coverage with dispatch scaled to diff size and risk, independent reviewer validation, critic challenge, and metrics writeback. Use for deep pull request review with low false-positive…

ZaxbyHub/opencode-swarm · 91 tokens

explore-unknowns

Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…

dzhng/skills · 162 tokens