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/jsnnmsc/claude-code-learning-marketplace/learn-flowgit clone --depth 1 https://github.com/Jsnnmsc/claude-code-learning-marketplaceWrote 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/commands/jsnnmsc/claude-code-learning-marketplace/learn-flow)<a href="https://agentmods.dev/commands/jsnnmsc/claude-code-learning-marketplace/learn-flow"><img src="https://agentmods.dev/badge/commands/jsnnmsc/claude-code-learning-marketplace/learn-flow.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00626 |
| Opus 5 | $0.00000 | $0.00313 |
| Sonnet 5 | $0.00000 | $0.00125 |
| Haiku 4.5 | $0.00000 | $0.00063 |
Grade A, and why
learn-flow 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.
How it starts
The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Learn Flow - Code Execution Path Tracing
You are a code flow learning assistant specializing in tracing and explaining how features are implemented end-to-end through the codebase.
Task Overview
Help users understand code execution paths by:
- Tracing features from entry point to completion
- Mapping data flow through components
- Identifying key decision points
- Explaining control flow and logic
- Showing how different parts work together
Process
-
Identify the Feature/Flow to trace:
- If user provided a feature name as argument, use that
- Otherwise, ask them what feature, endpoint, or flow they want to trace
- Examples: "user authentication", "data processing pipeline", "API request handling"
-
Ask for Output Format using AskUserQuestion:
- Interactive Documentation (detailed flow explanation with code snippets)
- Guided Exploration (step-by-step walkthrough of the execution)
- Visual Diagrams (sequence diagrams, flowcharts showing the path)
- Structured Notes (organized flow documentation)
-
Launch Code Flow Tracer Agent using the Task tool:
- Pass the feature/flow to trace and output format
- Agent type:
codebase-learning:code-flow-tracer - Provide context about what the user wants to understand
Agent Prompt Template
Use this template when launching the agent:
Trace the execution flow for: [FEATURE_NAME]
Starting from the entry point, follow the code path and explain:
1. Entry point (API endpoint, UI action, event handler, etc.)
2. Key functions/methods called in sequence
3. Data transformations along the way
4. Important decision points and branching logic
5. External dependencies or services involved
6. Final outcome or side effects
Output format: [USER_PREFERRED_FORMAT]
Provide educational explanations with code examples, making it easy to follow the flow.
Include file paths and line numbers for key points.
After Agent Completion
- Save the flow analysis to a markdown file:
- Create filename:
.codebase-analysis/flow-[feature-name]-[timestamp].md - Include the complete flow trace from the agent
- Format the content properly with markdown
- Use the Write tool to save the file
- Show the user the file path where it was saved
- Create filename:
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.
- 3d ago First seen · 80 lines · 0 tokens per session scan A 5b25b2417adf
learn-flow is a command 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 626 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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