Borrowing it
Nothing to install: this file belongs to asa-degroff/Porrima. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/asa-degroff/Porrima/main/AGENTS.mdgit clone --depth 1 https://github.com/asa-degroff/PorrimaWrote 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/instructions/asa-degroff/porrima/agents-md)<a href="https://agentmods.dev/instructions/asa-degroff/porrima/agents-md"><img src="https://agentmods.dev/badge/instructions/asa-degroff/porrima/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/asa-degroff/porrima/agents-md"><img src="https://agentmods.dev/badge/instructions/asa-degroff/porrima/agents-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.03082 | $0.03082 |
| Opus 5 | $0.01541 | $0.01541 |
| Sonnet 5 | $0.00616 | $0.00616 |
| Haiku 4.5 | $0.00308 | $0.00308 |
Grade A, and why
Porrima AGENTS.md 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 9d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Project
Porrima — A feature-rich agent framework and user interface with persistent memory, project context, image generation, and agentic tool execution. npm workspaces monorepo: server/ (Express + TypeScript) and client/ (React + Vite + Tailwind).
Quick Reference
- Server port: 3001 —
cd server && npm run dev(tsx watch mode) - Client port: 5173 —
cd client && npm run dev(Vite, proxies/apito server) - Build server:
cd server && npm run build(outputs toserver/dist/) - Build client:
cd client && npm run build(outputs toclient/dist/) - Type check:
npx tsc --noEmitfrom eitherserver/orclient/ - Data dir:
~/.porrima/(chats, projects, settings, memories, artifacts) - Models dir:
~/.local/share/llama-models/(symlinked GGUFs for llama.cpp router) - systemd services:
porrima.service— main server (auto-starts on boot)llama-server.service— llama.cpp router (port 32100, GPU inference)extraction-model.service— memory extraction server (port 32101, CPU-only)reranker.service— Qwen3-Reranker-0.6B (port 32102, CPU-only, memory retrieval)embedding-model.service— embedding server (port 32103, CPU-only)title-generation.service— title/recap server (port 32104, CPU-only)sync-llama-models.timer— auto-syncs HuggingFace GGUF downloads every 5 min
Architecture
See docs/architecture.md for full details.
Three chat types: agent (memory-augmented), quick (standalone), and system (synthesis, wake cycles, and automations). The chat route (server/src/routes/chat.ts) owns memory augmentation, SSE/persistence, compaction, and extraction around the shared agent loop in agent-loop-runner.ts. Chat storage is SQLite with FTS5 full-text search. LLM system uses OpenAI-compatible (llama.cpp) backend for all inference.
Tool System
See docs/tool-system.md for full details.
Native pi-ai tool calling with TypeBox schemas. Registry in agent-tools.ts with memory, filesystem, and sandbox tools. The low-level loop lives in agent-loop-runner.ts; the HTTP chat route and headless automation runner provide their own callbacks for transport, persistence, compaction, and follow-up prompts. ask_user pauses the HTTP loop and persists state. Message reconstruction splits persisted messages back into the pi-ai multi-message format.
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.
- 9d ago First seen · 180 lines · 3,082 tokens per session scan A 4953f91026a0
Porrima AGENTS.md is an instructions file published in the GitHub repository asa-degroff/Porrima (21 stars, last pushed today), licensed Apache-2.0. It adds 3,082 tokens to every session, about $0.0154 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 2026-08-30.
Other instructions, from other repositories
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vscode buildNext.instructions.md
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vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.