ingestion

ingestion is a cursor rule for Cursor from kubachour/mobile-growth-mcp. It costs 0 tokens per session (428 once invoked), scanned A, original, MIT.

A set of instructions for turning raw material—such as podcast transcripts, LinkedIn posts, and articles—into searchable records in a knowledge base.

In plain words
What is it for?
It helps extract insights into JSON, get user approval, save them under a standard filename, build and ingest the knowledge base, and verify search embeddings.
Why use it?
It gives content intake a repeatable process, so useful ideas are structured, reviewed, saved, and checked instead of being added inconsistently.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/.

Good fit It helps extract insights into JSON, get user approval, save them under a standard filename, build and ingest the knowledge base, and verify search embeddings.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/kubachour/mobile-growth-mcp/ingestion
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.

Clone the repo
git clone --depth 1 https://github.com/kubachour/mobile-growth-mcp

Made for: Cursor.

Wrote 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.

agentmods badge for ingestion

README.md
[![agentmods](https://agentmods.dev/badge/rules/kubachour/mobile-growth-mcp/ingestion/github.svg)](https://agentmods.dev/rules/kubachour/mobile-growth-mcp/ingestion)
Your own site
<a href="https://agentmods.dev/rules/kubachour/mobile-growth-mcp/ingestion"><img src="https://agentmods.dev/badge/rules/kubachour/mobile-growth-mcp/ingestion/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.

agentmods 80×15 button for ingestion

Your own site · 80×15
<a href="https://agentmods.dev/rules/kubachour/mobile-growth-mcp/ingestion"><img src="https://agentmods.dev/badge/rules/kubachour/mobile-growth-mcp/ingestion.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Nothing until a file matches its globs; then the whole rule loads.
When invoked 428 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00000 $0.00428
Opus 5 $0.00000 $0.00214
Sonnet 5 $0.00000 $0.00086
Haiku 4.5 $0.00000 $0.00043

Measured 9d ago against content hash d00131bf44e7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

ingestion 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.

.cursor/rules/ingestion.mdc · 47 lines

What it actually says

Content Ingestion

When the user provides raw content (podcast transcript, LinkedIn post, article) to add to the knowledge base, follow these steps. Full methodology is in skills/extract-insights.md and skills/ingest-content.md.

Quick Reference

  1. Extract — Parse raw content into structured insight JSON objects
  2. Review — Present summary table to user for approval
  3. Save — Write to data/insights/{author}-{source}-{descriptor}.json
  4. Ingest — Run npm run build && npm run ingest
  5. Verify — Check embeddings and search work

Insight JSON Schema

{
  "id": "mb-li-001",
  "title": "Descriptive title",
  "insight": "2-5 sentences, specific and actionable",
  "raw_excerpt": "Original text quote",
  "source_type": "podcast_transcript | linkedin_post | ...",
  "source_author": "Person name",
  "source_title": "Episode/post title",
  "source_date": "YYYY-MM-DD",
  "platform": "meta | google | tiktok",
  "topics": ["scaling", "creative_strategy"],
  "applies_to": ["subscription_apps", "ios"],
  "confidence": 4,
  "actionable_steps": ["Step 1", "Step 2"]
}

ID Format

{author_initials}-{source_code}-{NNN}

  • Source codes: li (LinkedIn), pt (podcast), cd (community), pdf (PDF), ct (conference), nt (notes)

Cross-Reference

After extracting, use search_insights to check for duplicates or reinforcing insights already in the database.

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. 9d ago First seen · 47 lines · 0 tokens per session scan A d00131bf44e7

Subscribe to this mod's changes

ingestion is a cursor rule published in the GitHub repository kubachour/mobile-growth-mcp (2 stars, last pushed 4mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 428 tokens. 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 2026-08-31.