freshrss-agent AGENTS.md

A repository guide that explains how an AI coding agent should work on the FreshRSS agent project. It describes the Python architecture, where the main components live, and the expected request flow between a user, agent, tools, and external services.

In plain words
What is it for?
Use it when developing, testing, or reviewing this Python 3.11+ project, especially its API clients, MCP server, agent server, and asynchronous tool execution.
Why use it?
It gives an agent the project context needed to make changes in the right places and follow the required workflow. This reduces guesswork about the code structure and commands.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/knuckles-team/freshrss-agent/agents-md
Clone the repo
git clone --depth 1 https://github.com/Knuckles-Team/freshrss-agent

Made for: Codex, OpenCode.

Per session 3,408 This file is loaded in full into every session.
When invoked 3,408 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin 89% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.03408 $0.03408
Opus 5 $0.01704 $0.01704
Sonnet 5 $0.00682 $0.00682
Haiku 4.5 $0.00341 $0.00341

Measured 2d ago against content hash b32d183d0efc, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

freshrss-agent 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 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.

Origin

This is a copy

89% identical to servicenow-api AGENTS.md — 91 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

AGENTS.md · 270 lines

How it starts

The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

Claude Code loads this file via CLAUDE.md (@AGENTS.md import) — the two stay in sync. Edit this file, not CLAUDE.md.

Tech Stack & Architecture

  • Language/Version: Python 3.11+
  • Core Libraries: agent-utilities, fastmcp, pydantic-ai
  • Key principles: Functional patterns, Pydantic for data validation, asynchronous tool execution.
  • Architecture:
    • freshrss_agent/api/: Modular folder for target service client wrappers.
    • freshrss_agent/mcp/: Modular folder for action-routed dynamic MCP tool tags.
    • freshrss_agent/mcp_server.py: Main MCP server entry point and tool registration.
    • freshrss_agent/agent_server.py: Pydantic AI agent definition and logic.

Architecture Diagram

graph TD
    User([User/A2A]) --> Server[A2A Server / FastAPI]
    Server --> Agent[Pydantic AI Agent]
    Agent --> Skills[Modular Skills]
    Agent --> MCP[MCP Server / FastMCP]
    MCP --> Client[API Client / Wrapper]
    Client --> ExternalAPI([External Service API])

Workflow Diagram

sequenceDiagram
    participant U as User
    participant S as Server
    participant A as Agent
    participant T as MCP Tool
    participant API as External API

    U->>S: Request
    S->>A: Process Query
    A->>T: Invoke Tool
    T->>API: API Request
    API-->>T: API Response
    T-->>A: Tool Result
    A-->>S: Final Response
    S-->>U: Output

Commands (run these exactly)

Installation

pip install .[all]

Quality & Linting (run from project root)

pre-commit run --all-files

Execution Commands

Run MCP Server

freshrss-mcp

Run Agent

freshrss-agent

Project Structure Quick Reference

  • MCP Entry Point → freshrss_agent/mcp_server.py
  • Agent Entry Point → freshrss_agent/agent_server.py
  • Source Code → freshrss_agent/
  • API client mixins → freshrss_agent/api/
  • MCP tool modules → freshrss_agent/mcp/
  • Tests → tests/
  • Documentation → docs/ (published via mkdocs + GitHub Pages)

Code Style & Conventions

Always:

  • Use agent-utilities for common patterns (e.g., create_mcp_server, create_agent_server).
  • Define input/output models using Pydantic.
  • Include descriptive docstrings for all tools (they are used as tool descriptions for LLMs).
  • Check for optional dependencies using try/except ImportError.

Read the full file on GitHub · 270 lines

Changes

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.

  1. 2d ago First seen · 270 lines · 3,408 tokens per session scan A b32d183d0efc

Subscribe to this mod's changes

freshrss-agent AGENTS.md is an instructions file published in the GitHub repository Knuckles-Team/freshrss-agent (0 stars, last pushed 5d ago), licensed MIT. It adds 3,408 tokens to every session, about $0.0170 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to servicenow-api AGENTS.md, differing in 91 lines, and is treated as a copy.

Related

Other instructions, from other repositories

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

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.

github/spec-kit · 7,104 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,182 tokens

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.

langchain-ai/langchain · 4,345 tokens

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).

microsoft/vscode · 5,001 tokens

next.js AGENTS.md

Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens