x-smart-read AGENTS.md

An instruction file for an X, formerly Twitter, research skill. It documents setup and command-line scripts for collecting posts, mentions, profile information, timelines, and engagement data.

In plain words
What is it for?
Use it to configure the skill, create morning or full briefings, review recent posts and engagement, inspect mentions, or find top posts from a local store.
Why use it?
It gives a coding agent the exact setup and commands for obtaining X data, including options to preview costs and limit the time range. This avoids having to remember the scripts or their arguments.

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/nevaaron/x-smart-read/agents-md
Clone the repo
git clone --depth 1 https://github.com/nevaaron/x-smart-read

Made for: Codex, OpenCode.

Per session 2,001 This file is loaded in full into every session.
When invoked 2,001 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found 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 $0.02001 $0.02001
Opus 5 $0.01001 $0.01001
Sonnet 5 $0.00400 $0.00400
Haiku 4.5 $0.00200 $0.00200

Measured 2d ago against content hash e0877c5ceb6f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

x-smart-read 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.

AGENTS.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — X (Twitter) Skill (Machine-Readable Reference)

This file is for AI agents (Claude Code, OpenClaw, Cursor, Copilot, etc.). For human docs, see README.md. For setup instructions, see SETUP.md.

Setup

Credentials directory: ~/.openclaw/skills-config/x-twitter/ Required files: config.json (created by setup)

uv run scripts/x_setup.py  # Interactive setup — imports keys, validates, picks budget tier

Commands

All scripts use uv run (auto-installs dependencies). Run from the skill directory. All commands support --dry-run to preview cost and --no-budget to skip budget checks.

x_briefing.py — Combined Morning Briefing

# Full briefing: posts + mentions + profile (~$0.020)
uv run scripts/x_briefing.py

# Custom lookback period
uv run scripts/x_briefing.py --hours 48

# Preview cost
uv run scripts/x_briefing.py --dry-run

x_timeline.py — Your Posts + Engagement

# Recent posts with engagement metrics (~$0.005)
uv run scripts/x_timeline.py recent
uv run scripts/x_timeline.py recent --max 5
uv run scripts/x_timeline.py recent --hours 24

# Top posts by engagement — FREE, reads from local store
uv run scripts/x_timeline.py top --days 7 --max 10

# Refresh one tweet's metrics (~$0.005)
uv run scripts/x_timeline.py refresh <TWEET_ID>

# Accountability check — how active on X? (~$0.005)
uv run scripts/x_timeline.py activity

# Preview cost without calling API
uv run scripts/x_timeline.py --dry-run recent

x_mentions.py — Mentions & Replies

# Recent mentions (~$0.005)
uv run scripts/x_mentions.py recent
uv run scripts/x_mentions.py recent --max 10 --hours 24

# Mentions with parent tweet context (~$0.005-0.030) [EXPENSIVE]
uv run scripts/x_mentions.py recent --context

x_read.py — Read Any Tweet or Thread

# Read a tweet by URL or ID (~$0.005)
uv run scripts/x_read.py https://x.com/user/status/123456
uv run scripts/x_read.py 123456

# Fetch full thread (~$0.005-0.010)
uv run scripts/x_read.py 123456 --thread

# Preview cost
uv run scripts/x_read.py --dry-run https://x.com/user/status/123456

Read the full file on GitHub · 206 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 · 206 lines · 2,001 tokens per session scan A e0877c5ceb6f

Subscribe to this mod's changes

x-smart-read AGENTS.md is an instructions file published in the GitHub repository nevaaron/x-smart-read (11 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 2,001 tokens to every session, about $0.0100 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.

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