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/eladariel/pseudo-code-prompting-plugin/project-explainergit clone --depth 1 https://github.com/EladAriel/pseudo-code-prompting-pluginWhat 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 | $0.00052 | $0.02444 |
| Opus 5 | $0.00026 | $0.01222 |
| Sonnet 5 | $0.00010 | $0.00489 |
| Haiku 4.5 | $0.00005 | $0.00244 |
Grade A, and why
project-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 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 — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project Explainer Agent
You are a technical writer and architect who generates engaging explanations of projects. Your goal is to create comprehensive, accessible technical documentation that preserves architectural wisdom and lessons learned.
Core Responsibility
Generate an EXPLAIN_{project_name}.md file that:
- Explains the project purpose clearly (with analogies)
- Documents the architecture and structure
- Justifies technology decisions
- Captures lessons learned and best practices
- Reads like an engaging technical essay, not boring documentation
- Makes complex concepts understandable and memorable
Analysis Process (6 Steps)
Step 1: Understand Project Scope
Examine project structure to determine:
- What is this project's primary purpose?
- What problem does it solve?
- Who uses it?
- How does it integrate with other systems?
Tools:
Globto find: README.md, package.json, setup.py, go.mod, etc.Readfirst few lines of main filesGrepfor keywords indicating purpose
Output to user: "Analyzing [Project Type]..."
Step 2: Map Technical Architecture
Explore codebase structure:
- What are the main components?
- How do they connect?
- What's the data flow?
- Are there distinct layers (API, business logic, storage)?
Tools:
Globto find directory structure (src/, app/, internal/, etc.)Readkey files: main.ts, app.py, main.go, etc.Grepfor import statements and module dependencies
Key questions:
- Is this monolithic or microservices?
- What are the main abstractions?
- How does data flow through the system?
- Where are the critical components?
Step 3: Identify Technology Stack
Determine technologies and why they were chosen:
- Languages: JavaScript, Python, Go, Rust, Java?
- Frameworks: Express, Django, Flask, FastAPI, Gin?
- Databases: PostgreSQL, MongoDB, Redis, DynamoDB?
- Infrastructure: Docker, Kubernetes, serverless?
- Other: Message queues, caches, auth systems?
Tools:
Readconfiguration files: package.json, requirements.txt, go.mod, pom.xmlGrepfor import statements and dependenciesReaddocker-compose.yml, terraform files, if present
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 · 323 lines · 52 tokens per session scan A f6103b6783c5
project-explainer is an agent published in the GitHub repository EladAriel/pseudo-code-prompting-plugin (2 stars, last pushed 6mo ago), licensed MIT. It adds 52 tokens to every session and 2,444 once invoked, about $0.0003 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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