inbox

A workflow for processing unreviewed Web Clipper notes, which are saved excerpts from websites, into organized notes. It creates or updates concept notes and content ideas in a structured knowledge base.

In plain words
What is it for?
Use it to process Markdown files from an inbox, extract their main insights, and save linked concept notes and content ideas.
Why use it?
It turns a pile of unsorted clips into reusable notes with topics, sources, key ideas, and possible content directions.

Skill for Claude CodeCodex

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 skills/railly/agent-brain/inbox
Any agent
npx skills add Railly/agent-brain --skill inbox
Clone the repo
git clone --depth 1 https://github.com/Railly/agent-brain

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,185 The whole file, excluding the scripts and references it only reads on demand.
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 $0.00014 $0.01185
Opus 5 $0.00007 $0.00593
Sonnet 5 $0.00003 $0.00237
Haiku 4.5 $0.00001 $0.00119

Measured 2d ago against content hash d15ce86973e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

inbox 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/skills/inbox/SKILL.md · 138 lines

How it starts

The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Process pending clips from 01_Inbox/.

IMPORTANT: Be direct

  • Don't check if folders exist - they do
  • Don't search for existing notes - just write
  • Don't read ideas.md before appending - just append
  • Minimize tool calls

Flow

  1. Find unprocessed clips List all .md files directly in 01_Inbox/ - these are unprocessed.

  2. For each clip (read content, extract insight, identify topic)

  3. Create atomic note in 03_Garden/concepts/{topic-slug}.md (FLAT, evergreen):

    ---
    type: concept
    created: {{date}}
    themes: []
    sources:
      - "[[01_Inbox/processed/{{date}}/{processed-slug}]]"
    people: []
    ---
    # {Topic}
    
    {1-2 sentence insight}
    
    ## Key ideas
    - {extracted points}
    
    ## Connections
    - [[Related concept]] - how it relates
    

    If concept already exists: Append to Key ideas + add new source to sources: array

  4. Extract content ideas to 05_Areas/content-creation/ideas/{{date}}/{slug}.md:

    ---
    type: content-idea
    format: tweet | thread | blog | short | tutorial
    status: idea
    source: "[[03_Garden/concepts/{concept-slug}]]"
    created: {{date}}
    priority: 3
    ---
    # {Title}
    
    {The content idea - actual tweet text, thread hook, or blog thesis}
    
    ## Hook
    {Why this will resonate}
    
    ## Notes
    - {Additional context}
    
  5. Enrich with metadata:

    • People: If author or people mentioned, create 03_Garden/people/{person-name}.md if doesn't exist
    • Location: If place mentioned, add coordinates to concept note
  6. Find connections

    • List existing notes: 03_Garden/concepts/
    • Look for related topics (semantic similarity, shared tags)
    • Add backlinks to the new concept and existing related concepts
  7. Mark clip as processed - add generated: links + move to date folder:

    First, update the clip's frontmatter to add the generated: field:

    ---
    generated:
      - "[[03_Garden/concepts/{concept-slug}]]"
      - "[[05_Areas/.../ideas/{{date}}/{idea-slug}]]"
    ---
    

Read the full file on GitHub · 138 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 · 138 lines · 14 tokens per session scan A d15ce86973e7

Subscribe to this mod's changes

inbox is a skill published in the GitHub repository Railly/agent-brain (22 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 1,185 once invoked, about $0.0001 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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