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/sairam0424/mindforge/code-tourgit clone --depth 1 https://github.com/sairam0424/MindForgeWrote 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/sairam0424/mindforge/code-tour)<a href="https://agentmods.dev/commands/sairam0424/mindforge/code-tour"><img src="https://agentmods.dev/badge/commands/sairam0424/mindforge/code-tour.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 5.1 | $0.00034 | $0.00930 |
| Opus 5 | $0.00017 | $0.00465 |
| Sonnet 5 | $0.00007 | $0.00186 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
code-tour 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<execution_context> @.mindforge/skills/code-tour/SKILL.md @.mindforge/skills/codebase-onboarding/SKILL.md </execution_context>
-
Trace hot paths: Starting from entry points, trace the most important execution paths:
- The "happy path" for the core use case
- Request lifecycle (middleware → handler → service → repository → response)
- Data flow from input to persistence
- Event/message processing pipeline (if event-driven)
- Mark each file touched with its role in the path
-
Build progressive reading order: Organize files into a numbered tour sequence:
- Level 1: Entry points and configuration (understand how it starts)
- Level 2: Core domain models and types (understand what it models)
- Level 3: Service layer and business logic (understand what it does)
- Level 4: Infrastructure and adapters (understand how it connects)
- Level 5: Tests and edge cases (understand how it's verified)
- Each level builds on knowledge from the previous level
-
Annotate each stop: For every file in the tour, provide:
- Stop number and title (e.g., "Stop 3: User Authentication Service")
- Why this file matters (1-2 sentences on its role in the system)
- Key sections to focus on (specific line ranges or function names)
- Patterns to notice (design patterns, conventions, architectural decisions)
- Connections (what calls this, what this calls — upstream/downstream)
-
Add understanding checkpoints: After every 3-5 stops, insert a checkpoint:
- Summary of what the reader should now understand
- Questions to test comprehension ("Can you explain why X uses Y?")
- Mental model diagram (ASCII box-and-arrow showing relationships learned so far)
- Common misconceptions to avoid at this stage
-
Document architecture decisions in context: At relevant tour stops, explain:
- Why this approach was chosen over alternatives
- Historical context if visible from git blame or comments
- Trade-offs accepted and their implications
- When this decision should be revisited
-
Handle depth modes:
--depth shallow: Entry points + core domain + one hot path (10-15 stops)--depth deep: Full system trace including infrastructure, error handling, and edge cases (25-40 stops)- Default: moderate depth covering all layers with representative examples (15-25 stops)
-
Cross-reference with tests: For each major component in the tour:
- Point to the relevant test file
- Highlight which behaviors are tested vs untested
- Note any test patterns that reveal intended usage
-
Write TOUR.md: Output the complete tour document:
- Table of contents with all stops
- Prerequisites (tools, environment, background knowledge)
- Estimated reading time per section
- Numbered stops with full annotations
- Checkpoints between sections
- "Where to go next" section for deeper exploration
- Glossary of project-specific terms
-
Generate companion commands: Produce helper commands:
- Script to open all tour files in editor in order
- Grep patterns to find related code not in the tour
- Links to relevant external documentation
- Suggested follow-up tours for specific subsystems
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 · 86 lines · 34 tokens per session scan A 3d386f6137eb
code-tour is a command published in the GitHub repository sairam0424/MindForge (0 stars, last pushed 2d ago), licensed MIT. It adds 34 tokens to every session and 930 once invoked, about $0.0002 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 2026-09-03.
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