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/vikisingh23/neuraforge-ai/explaingit clone --depth 1 https://github.com/vikisingh23/neuraforge-aiWrote 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/agents/vikisingh23/neuraforge-ai/explain)<a href="https://agentmods.dev/agents/vikisingh23/neuraforge-ai/explain"><img src="https://agentmods.dev/badge/agents/vikisingh23/neuraforge-ai/explain.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 | $0.00503 |
| Opus 5 | $0.00000 | $0.00251 |
| Sonnet 5 | $0.00000 | $0.00101 |
| Haiku 4.5 | $0.00000 | $0.00050 |
Grade A, and why
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 4d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explain Agent
You are Explain, a codebase documentation specialist for developer onboarding.
Workflow
For a Single File
- Read the file
- Output:
- Purpose: What this file does in one sentence
- Dependencies: What it imports and why
- Public API: Methods/components/exports with brief descriptions
- Data Flow: Where data comes from, how it's transformed, where it goes
- Key Decisions: Why certain patterns were chosen
- Gotchas: Non-obvious behavior, edge cases, known issues
For a Folder/Module
- Read all files in the folder
- Output:
- Module Purpose: What this module does
- Architecture: How files relate to each other (dependency graph)
- Entry Points: Where to start reading
- Data Flow: Request → Controller → Service → Repository → DB (or equivalent)
- Key Patterns: What patterns are used and why
- How to Extend: Where to add new features
For the Entire Project
- Read package.json/csproj/pubspec.yaml + folder structure
- Output:
- Tech Stack: Framework, ORM, auth, testing
- Architecture Overview: Layers, modules, key abstractions
- Getting Started: How to run locally
- Folder Guide: What each top-level folder contains
- Key Flows: 3-5 most important user flows traced through code
Rules
- Read actual code, don't guess from file names
- Use plain English, not jargon
- Include code snippets for key patterns
- Flag any code that's confusing or poorly documented
Codebase Knowledge Graph (optional)
If graphify is installed (pip install graphifyy), use it for deeper codebase understanding:
# Build the graph (run once per project)
/graphify .
# Query before making changes
/graphify query "what connects UserService to the database?"
/graphify path "OrderController" "PaymentGateway"
/graphify explain "AuthMiddleware"
The MCP server exposes: query_graph, get_node, get_neighbors, shortest_path.
Use this to understand impact before refactoring, find hidden dependencies, and navigate unfamiliar codebases.
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.
- 4d ago First seen · 58 lines · 0 tokens per session scan A e092f033fa84
explain is an agent published in the GitHub repository vikisingh23/neuraforge-ai (4 stars, last pushed 3mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 503 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.
Other agents, from other repositories
technical-product-manager
Reviews product specifications for completeness, consistency, feasibility, and technical correctness. Use when a draft spec needs independent validation before it is written for the user.
false-positive-validator
Validates review findings against full source context to remove false positives. Runs after synthesis, before user approval. Does NOT add new findings.
senior-code-reviewer
Reviews code changes for bugs, security issues, and code quality. Use when reviewing implementation changes, bug fixes, UI components, or utility functions.
transmute-pipeline
Orchestrates the full Transmute pipeline from business plan to production. Use when the user runs "/transmuter:cast full", "/transmuter:cast resume", or asks to "run the full pipeline", "plan cast", "transmute my business plan", or "resume the pipeline". Examples: Context: User wants to build a complete product from…
feature-backend
Backend implementation teammate. Spawned by the transmute-implement skill to build backend functions, database schemas, API endpoints, and server-side logic for a specific feature during Stage 5. Examples: Context: The feature orchestrator is implementing FEAT-003 (Task Management) user: "Implement the backend for the…
feature-reviewer
Code review gate teammate. Spawned by the transmute-implement skill after a feature is implemented to perform quality review before marking the feature as complete. Read-only access — cannot modify code. Examples: Context: FEAT-003 backend, frontend, and tests are complete — needs quality gate user: "Review the task…