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 agentmods add commands/xsovad06/sova/develop-explaingit clone --depth 1 https://github.com/xsovad06/sovaWhat 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 | $0.00020 | $0.00699 |
| Opus 5 | $0.00010 | $0.00349 |
| Sonnet 5 | $0.00004 | $0.00140 |
| Haiku 4.5 | $0.00002 | $0.00070 |
Grade A, and why
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 yesterday.
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 — 115 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: $ARGUMENTS
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 |
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.
- yesterday First seen · 115 lines · 20 tokens per session scan A 0425a3937df6
develop-explain is a command published in the GitHub repository xsovad06/sova (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 699 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 2026-08-31.
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retro
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dashboard
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learn
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quiz
Quiz yourself on a topic from your learning plan with adaptive difficulty and mixed question formats.