Borrowing it
Nothing to install: this file belongs to walm00/business-context-os. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/walm00/business-context-os/main/.claude/skills/context-ingest/SKILL.mdgit clone --depth 1 https://github.com/walm00/business-context-osWrote 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.
[](https://agentmods.dev/skills/walm00/business-context-os/context-ingest)<a href="https://agentmods.dev/skills/walm00/business-context-os/context-ingest"><img src="https://agentmods.dev/badge/skills/walm00/business-context-os/context-ingest/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.
<a href="https://agentmods.dev/skills/walm00/business-context-os/context-ingest"><img src="https://agentmods.dev/badge/skills/walm00/business-context-os/context-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00150 | $0.04814 |
| Opus 5 | $0.00075 | $0.02407 |
| Sonnet 5 | $0.00030 | $0.00963 |
| Haiku 4.5 | $0.00015 | $0.00481 |
Grade A, and why
context-ingest 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.
How it starts
The opening of the file, as written. The whole thing — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Context Ingest
Purpose
This skill IS:
- The entry point for getting new knowledge INTO your context architecture
- A router that sends information to the correct owning data point
- A classifier that determines what type of knowledge you're adding
- The mechanism that makes your context system compound over time
This skill IS NOT:
- Creating the initial context architecture (use
context-onboardingfor that) - Auditing existing context (use
context-auditfor that) - A raw file storage system (it extracts and integrates, not archives)
When to Use
- "Here's our new brand guidelines PDF — integrate it" → integrate into active docs
- "Save these meeting notes for later" → dump to
_inbox/ - "I have an idea about enterprise pricing" → park in
_planned/ - "I read this article — not sure if it's relevant" → triage — Claude reads, recommends a path
- "Our competitor just launched a new product" → integrate into competitive positioning
- "Watch this YouTube video and capture what matters" → triage — Claude extracts, asks where
- "I pasted some notes — figure out where they belong" → triage — Claude classifies, user decides
- "Fetch our brand doc from Google Drive" → fetch + integrate via MCP connector
- "We have hundreds of call recordings in Notion" → map as external reference, don't copy
Front-door dispatch (use first)
context-ingest is the single public entry point for new material. Detect the input shape before asking the user, and dispatch to the specialist skill when one fits — don't make the user know which slash command to type.
| Input shape | Dispatch to | Why |
|---|---|---|
| HTTP/HTTPS URL (article, GitHub, YouTube) | /wiki run <url> (the bcos-wiki skill, Path A) |
Wiki owns external-source ingest, banner citations, schema validation, refresh tier |
Path inside docs/_inbox/ and user says "make this a wiki page" |
/wiki promote <path> (Path B) |
Wiki owns the _inbox/ → _wiki/pages/ promotion |
| Local file or pasted text — runbook, SOP, decision narrative, post-mortem, glossary entry, FAQ, transcript, research clipping, customer-call notes | /wiki create from <path-or-paste> (Path B) |
Per plugin-storage-contract.md Rule 2, the wiki is the universal long-form / cross-cutting content destination. Don't route to _collections/ (legal-weight only) or docs/operations/<custom> (that's a folder pattern that bypasses wiki tooling). |
| Slack export, meeting transcript, chat log, call recording transcript | context-mine first → its output lands in _inbox/ → resume context-ingest triage on the result |
Mine is the extraction preprocessor; ingest is the classifier/router. The processed _inbox/ capture then typically routes to /wiki promote (transcripts are informational long-form content — Rule 2). |
| Loose notes, pasted text, brain dump, "save this for later" | Stay in context-ingest (use AskUserQuestion below) |
This skill owns inbox/planned/active classification |
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.
- 9d ago First seen · 379 lines · 150 tokens per session scan A 36aba6a2f55e
context-ingest is a skill published in the GitHub repository walm00/business-context-os (21 stars, last pushed 3mo ago), licensed MIT. It adds 150 tokens to every session and 4,814 once invoked, about $0.0007 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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