Add a source file to the processing queue. An agent skill from agenticnotetaking/arscontexta.

MITAuto-check: notesProductivity & Automation

Install Seed

skills CLI
$ npx skills add agenticnotetaking/arscontexta --skill seed -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install agenticnotetaking/arscontexta seed --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/agenticnotetaking/arscontexta.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skill-sources/seed .claude/skills/seed && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seed
GitHub stars
3.5k
Token cost
~2.4k tokens
SKILL.md length
748 words
Files
2
Skills in repo
25
Repo updated
First seen
Licence
MIT

At a glance

Add a source file to the processing queue. An agent skill from agenticnotetaking/arscontexta.

  • Queue this for processing
  • SKILL.md covers EXECUTE NOW, Step 1: Validate Source, Step 2: Duplicate Detection and Step 3: Create Archive Structure, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Email management

What it does

Seed is an agent skill from agenticnotetaking/arscontexta. Add a source file to the processing queue. Checks for duplicates, creates archive folder, moves source from inbox, creates extract task, and updates queue. Triggers on "/seed", "/seed [file]", "queue this for processing".

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.json`).

It sits in Productivity & Automation, covering Email management. The repository describes itself as: Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as… The licence is MIT.

When your agent uses it

  • Queue this for processing
  • Tasks that involve Email management

Example prompts

  • “/seed [file]”
  • “queue this for processing”
  • “/seed”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash

What it can do on your machine

Read from SKILL.md and the folder at commit 2acfd5c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash, markdown, yaml and json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Seed loads about 2.4k tokens when it runs. Until then it costs about 57 tokens; SKILL.md has 748 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~57
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Grep, Glob, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from agenticnotetaking/arscontexta at commit 2acfd5c, republished under its MIT licence (© agenticnotetaking). 748 words, ~2,420 tokens.

Download SKILL.mdSave it as .claude/skills/seed/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
seed
description
Add a source file to the processing queue. Checks for duplicates, creates archive folder, moves source from inbox, creates extract task, and updates queue. Triggers on "/seed", "/seed [file]", "queue this for processing".
allowed-tools
Read, Write, Edit, Grep, Glob, Bash
version
1.0
generated_from
arscontexta-v1.6
user-invocable
true
context
fork
model
sonnet
argument-hint
[file] — path to source file to seed for processing

EXECUTE NOW

Target: $ARGUMENTS

The target MUST be a file path. If no target provided, list {DOMAIN:inbox}/ contents and ask which to seed.

Step 0: Read Vocabulary

Read ops/derivation-manifest.md (or fall back to ops/derivation.md) for domain vocabulary mapping. All output must use domain-native terms. If neither file exists, use universal terms.

START NOW. Seed the source file into the processing queue.


Step 1: Validate Source

Confirm the target file exists. If it does not, check common locations:

  • {DOMAIN:inbox}/{filename}
  • Subdirectories of {DOMAIN:inbox}/

If the file cannot be found, report error and stop:

ERROR: Source file not found: {path}
Checked: {locations checked}

Read the file to understand:

  • Content type: what kind of material is this? (research article, documentation, transcript, etc.)
  • Size: line count (affects chunking decisions in /reduce)
  • Format: markdown, plain text, structured data

Step 2: Duplicate Detection

Check if this source has already been processed. Two levels of detection:

2a. Filename Match

Search the queue file and archive folders for matching source names:

bash
SOURCE_NAME=$(basename "$FILE" .md | tr ' ' '-' | tr '[:upper:]' '[:lower:]')

# Check queue for existing entry
# Search in ops/queue.yaml, ops/queue/queue.yaml, or ops/queue/queue.json
grep -l "$SOURCE_NAME" ops/queue*.yaml ops/queue/*.yaml ops/queue/*.json 2>/dev/null

# Check archive folders
ls -d ops/queue/archive/*-${SOURCE_NAME}* 2>/dev/null
2b. Content Similarity (if semantic search available)

If semantic search is available (qmd MCP tools or CLI), check for content overlap:

mcp__qmd__search query="claims from {source filename}" limit=5

Or via keyword search in the {DOMAIN:notes}/ directory:

bash
grep -rl "{key terms from source title}" {DOMAIN:notes}/ 2>/dev/null | head -5
2c. Report Duplicates

If either check finds a match:

  • Show what was found (filename match or content overlap)
  • Ask: "This source may have been processed before. Proceed anyway? (y/n)"
  • If the user declines, stop cleanly
  • If the user confirms (or no duplicate found), continue

Step 3: Create Archive Structure

Create the archive folder. The date-prefixed folder name ensures uniqueness.

bash
DATE=$(date -u +"%Y-%m-%d")
SOURCE_BASENAME=$(basename "$FILE" .md | tr ' ' '-' | tr '[:upper:]' '[:lower:]')
ARCHIVE_DIR="ops/queue/archive/${DATE}-${SOURCE_BASENAME}"
mkdir -p "$ARCHIVE_DIR"

The archive folder serves two purposes:

  1. Permanent home for the source file (moved from {DOMAIN:inbox})
  2. Destination for task files after batch completion (/archive-batch moves them here)

Step 4: Move Source to Archive

Move the source file from its current location to the archive folder. This is the claiming step — once moved, the source is owned by this processing batch.

{DOMAIN:inbox} sources get moved:

bash
if [[ "$FILE" == *"{DOMAIN:inbox}"* ]] || [[ "$FILE" == *"inbox"* ]]; then
  mv "$FILE" "$ARCHIVE_DIR/"
  FINAL_SOURCE="$ARCHIVE_DIR/$(basename "$FILE")"
fi

Sources outside {DOMAIN:inbox} stay in place:

bash
# Living docs (like configuration files) stay where they are
# Archive folder is still created for task files
FINAL_SOURCE="$FILE"

Use $FINAL_SOURCE in the task file — this is the path all downstream phases reference.

Why move immediately: All references (task files, {DOMAIN:note_plural}' Source footers) use the final archived path from the start. No path updates needed later. If it is in {DOMAIN:inbox}, it is unclaimed. Claimed sources live in archive.

Step 5: Determine Claim Numbering

Find the highest existing claim number across the queue and archive to ensure globally unique claim IDs.

bash
# Check queue for highest claim number in file references
QUEUE_MAX=$(grep -oE '[0-9]{3}\.md' ops/queue*.yaml ops/queue/*.yaml 2>/dev/null | \
  grep -oE '[0-9]{3}' | sort -n | tail -1)
QUEUE_MAX=${QUEUE_MAX:-0}

# Check archive for highest claim number
ARCHIVE_MAX=$(find ops/queue/archive -name "*-[0-9][0-9][0-9].md" 2>/dev/null | \
  grep -v summary | sed 's/.*-\([0-9][0-9][0-9]\)\.md/\1/' | sort -n | tail -1)
ARCHIVE_MAX=${ARCHIVE_MAX:-0}

# Next claim starts after the highest
NEXT_CLAIM_START=$((QUEUE_MAX > ARCHIVE_MAX ? QUEUE_MAX + 1 : ARCHIVE_MAX + 1))

Claim numbers are globally unique and never reused across batches. This ensures every claim file name ({source}-{NNN}.md) is unique vault-wide.

Step 6: Create Extract Task File

Write the task file to ops/queue/${SOURCE_BASENAME}.md:

markdown
---
id: {SOURCE_BASENAME}
type: extract
source: {FINAL_SOURCE}
original_path: {original file path before move}
archive_folder: {ARCHIVE_DIR}
created: {UTC timestamp}
next_claim_start: {NEXT_CLAIM_START}
---

# Extract {DOMAIN:note_plural} from {source filename}

## Source
Original: {original file path}
Archived: {FINAL_SOURCE}
Size: {line count} lines
Content type: {detected type}

## Scope
{scope guidance if provided via --scope, otherwise: "Full document"}

## Acceptance Criteria
- Extract claims, implementation ideas, tensions, and testable hypotheses
- Duplicate check against {DOMAIN:notes}/ during extraction
- Near-duplicates create enrichment tasks (do not skip)
- Each output type gets appropriate handling

## Execution Notes
(filled by /reduce)

## Outputs
(filled by /reduce)

Step 7: Update Queue

Add the extract task entry to the queue file.

For YAML queues (ops/queue.yaml):

yaml
- id: {SOURCE_BASENAME}
  type: extract
  status: pending
  source: "{FINAL_SOURCE}"
  file: "{SOURCE_BASENAME}.md"
  created: "{UTC timestamp}"
  next_claim_start: {NEXT_CLAIM_START}

For JSON queues (ops/queue/queue.json):

json
{
  "id": "{SOURCE_BASENAME}",
  "type": "extract",
  "status": "pending",
  "source": "{FINAL_SOURCE}",
  "file": "{SOURCE_BASENAME}.md",
  "created": "{UTC timestamp}",
  "next_claim_start": {NEXT_CLAIM_START}
}

If no queue file exists: Create one with the appropriate schema header (phase_order definitions) and this first task entry.

Show full SKILL.md (292 more words)Show less

Step 8: Report

--=={ seed }==--

Seeded: {SOURCE_BASENAME}
Source: {original path} -> {FINAL_SOURCE}
Archive folder: {ARCHIVE_DIR}
Size: {line count} lines
Content type: {detected type}

Task file: ops/queue/{SOURCE_BASENAME}.md
Claims will start at: {NEXT_CLAIM_START}
Claim files will be: {SOURCE_BASENAME}-{NNN}.md (unique across vault)
Queue: updated with extract task

Next steps:
  /ralph 1 --batch {SOURCE_BASENAME}     (extract claims)
  /pipeline will handle this automatically

Why This Skill Exists

Manual queue management is error-prone. This skill:

  • Ensures consistent task file format across batches
  • Handles claim numbering automatically (globally unique)
  • Checks for duplicates before creating unnecessary work
  • Moves sources to their permanent archive location immediately
  • Provides clear next steps for the user

Naming Convention

Task files use the source basename for human readability:

  • Task file: {source-basename}.md
  • Claim files: {source-basename}-{NNN}.md
  • Summary: {source-basename}-summary.md
  • Archive folder: {date}-{source-basename}/

Claim numbers (NNN) are globally unique across all batches, ensuring every filename is unique vault-wide. This is required because wiki links resolve by filename, not path.

Source Handling Patterns

{DOMAIN:inbox} source (most common):

{DOMAIN:inbox}/research/article.md
    | /seed
    v
ops/queue/archive/2026-01-30-article/article.md  <- source moved here
ops/queue/article.md                               <- task file created

Living doc (outside {DOMAIN:inbox}):

CLAUDE.md -> stays as CLAUDE.md (no move)
ops/queue/archive/2026-01-30-claude-md/           <- folder still created
ops/queue/claude-md.md                             <- task file created

When /archive-batch runs later, it moves task files into the existing archive folder and generates a summary.


Edge Cases

Source outside {DOMAIN:inbox}: Works — source stays in place, archive folder is created for task files only.

No queue file: Create ops/queue/queue.yaml (or .json) with schema header and this first entry.

Large source (2500+ lines): Note in output: "Large source ({N} lines) -- /reduce will chunk automatically."

Source is a URL or non-file: Report error: "/seed requires a file path."

No ops/derivation-manifest.md: Use universal vocabulary for all output.


Critical Constraints

never:

  • Skip duplicate detection (prevents wasted processing)
  • Move a source that is not in {DOMAIN:inbox} (living docs stay in place)
  • Reuse claim numbers from previous batches (globally unique is required)
  • Create a task file without updating the queue (both must happen together)

always:

  • Ask before proceeding when duplicates are detected
  • Create the archive folder even for living docs (task files need it)
  • Use the archived path (not original) in the task file for {DOMAIN:inbox} sources
  • Report next steps clearly so the user knows what to do next
  • Compute next_claim_start from both queue AND archive (not just one)

© agenticnotetaking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skill-sources/seed of agenticnotetaking/arscontexta.

  • SKILL.md
  • skill.json

Open the folder on GitHubat commit 2acfd5c

Compare with similar skills

Seed next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Seed compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Seed this skillagenticnotetaking/arscontexta3.5k—~2.4kAutomated safety check: NotesMIT
Process Inboxtelegramdesktop/tdesktop33k2 repos~4.5kAutomated safety check: PassGPL-3.0
Continuetelegramdesktop/tdesktop33k2 repos~9.4kAutomated safety check: PassGPL-3.0
Garden Inboxpaperclipai/paperclip99k—~1.1kAutomated safety check: PassMIT
Career-Ops Gmail Lead Plugincareer-ops-hq/career-ops74k—~233Automated safety check: NotesMIT
Skill CompassEvol-ai/SkillCompass2161 repos~3.1kAutomated safety check: PassMIT

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Questions about Seed

What does Seed do?

Add a source file to the processing queue. An agent skill from agenticnotetaking/arscontexta. Seed is an agent skill from agenticnotetaking/arscontexta. Add a source file to the processing queue.

When should I use Seed?

Seed fits situations like: queue this for processing; tasks that involve Email management.

How do I install Seed in Claude Code?

Run `npx skills add agenticnotetaking/arscontexta --skill seed -a claude-code`. Or copy the skill folder (skill-sources/seed in agenticnotetaking/arscontexta) into .claude/skills/seed in your project. Claude Code loads it when a task matches its description.

How do I install Seed in Codex?

Run `npx skills add agenticnotetaking/arscontexta --skill seed -a codex`. Or copy the skill folder (skill-sources/seed in agenticnotetaking/arscontexta) into .agents/skills/seed in your project. Codex loads it when a task matches its description.

Can I use Seed in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add agenticnotetaking/arscontexta --skill seed -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seed, .gemini/skills/seed, .github/skills/seed and .opencode/skills/seed in your project.

What does Seed need to run?

SKILL.md names no scripts, command-line tools or credentials: Seed is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash.

Does Seed access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Seed safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Seed use?

Seed is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Seed use?

About 2.4k tokens (SKILL.md is roughly 9.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Seed?

Skills that share tags, products or a category with Seed: Process Inbox (telegramdesktop/tdesktop, 33k stars), Continue (telegramdesktop/tdesktop, 33k stars), Garden Inbox (paperclipai/paperclip, 99k stars) and Career-Ops Gmail Lead Plugin (career-ops-hq/career-ops, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Seed?

agenticnotetaking (a GitHub organization) maintains it in agenticnotetaking/arscontexta, which has 3,492 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on February 24, 2026.

Source: agenticnotetaking/arscontexta on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.