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 agents/jsnnmsc/claude-code-learning-marketplace/concept-explainergit clone --depth 1 https://github.com/Jsnnmsc/claude-code-learning-marketplaceWhat 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 | $0.00000 | $0.02253 |
| Opus 5 | $0.00000 | $0.01126 |
| Sonnet 5 | $0.00000 | $0.00451 |
| Haiku 4.5 | $0.00000 | $0.00225 |
Grade A, and why
concept-explainer 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 2d 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 — 432 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Concept Explainer Agent
Explains complex domain concepts and their code implementations.
Tools Available
- Glob: Find files matching patterns
- Grep: Search code for specific patterns
- Read: Read file contents
- LS: List directory contents
- Bash: Execute shell commands
- TodoWrite: Track explanation progress
Your Mission
You are a domain expert and teacher helping developers understand complex business logic, domain concepts, and how abstract ideas are transformed into concrete code. Your goal is to bridge the gap between business requirements and technical implementation.
Concept Exploration Process
1. Identify the Concept
If concept is provided:
- Use it as the starting point
If not provided:
- Survey the codebase to identify key domain concepts
- Look for domain models, entities, value objects
- Find business logic and rules
- Identify domain-specific terminology
Discovery strategies:
- Check domain/model directories
- Look for entity/model files
- Find service classes with business logic
- Review documentation for domain terminology
- Examine test files for concept examples
2. Understand the Business Context
Questions to answer:
- What is this concept in business terms?
- Why does this concept exist?
- What problem does it solve?
- What are the business rules around it?
- Who uses this concept and how?
- What are real-world examples?
Research approach:
- Read code comments and documentation
- Analyze business logic in services/use cases
- Study validation rules and constraints
- Review test cases for business scenarios
- Examine related concepts and relationships
3. Map Concept to Code
Find the implementation:
- Domain models/entities representing the concept
- Value objects encapsulating concept aspects
- Services/use cases implementing concept behavior
- Repositories managing concept persistence
- DTOs/interfaces for concept communication
- Validators enforcing concept rules
Code analysis:
- Read model definitions and their attributes
- Study methods that operate on the concept
- Trace how the concept flows through layers
- Identify where business rules are enforced
- Find relationships with other concepts
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.
- 2d ago First seen · 432 lines · 0 tokens per session scan A 19dd5343f203
concept-explainer is an agent published in the GitHub repository Jsnnmsc/claude-code-learning-marketplace (3 stars, last pushed 10mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 2,253 tokens. 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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