ingest-filter

ingest-filter is a skill for Claude Code, Codex from NxcoreAI/EverRoom. It costs 17 tokens per session (161 once invoked), scanned A, original, no licence file.

A review step that decides whether imported materials contain information worth keeping in EverRoom.

In plain words
What is it for?
It is for evaluating documents, uploads, or other ingested material during EverRoom processing.
Why use it?
It helps filter out material that is not useful for long-term storage before it becomes part of the system’s memory.

Skill for Claude CodeCodex

Which agent this was written for is unclear — body not stored (licence); the path alone says nothing.

Good fit It is for evaluating documents, uploads, or other ingested material during EverRoom processing.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nxcoreai/everroom/ingest-filter
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.

Any agent
npx skills add NxcoreAI/EverRoom --skill ingest-filter
Clone the repo
git clone --depth 1 https://github.com/NxcoreAI/EverRoom

Made for: Claude Code, Codex.

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 ingest-filter

README.md
[![agentmods](https://agentmods.dev/badge/skills/nxcoreai/everroom/ingest-filter.svg)](https://agentmods.dev/skills/nxcoreai/everroom/ingest-filter)
Your own site
<a href="https://agentmods.dev/skills/nxcoreai/everroom/ingest-filter"><img src="https://agentmods.dev/badge/skills/nxcoreai/everroom/ingest-filter.svg" alt="Measured on agentmods" height="20"></a>
Per session 17 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 161 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 unknown 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 $0.00017 $0.00161
Opus 5 $0.00009 $0.00081
Sonnet 5 $0.00003 $0.00032
Haiku 4.5 $0.00002 $0.00016

Measured 8d ago against content hash 357b29327d99, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

ingest-filter 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 8d 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/knowledge/skills/ingest-filter/SKILL.md · 11 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

Read it on GitHub

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. 8d ago First seen · 11 lines · 17 tokens per session scan A 357b29327d99

Subscribe to this mod's changes

ingest-filter is a skill published in the GitHub repository NxcoreAI/EverRoom (891 stars, last pushed 2d ago), with no licence file. It adds 17 tokens to every session and 161 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.

Related

Other skills, from other repositories

wegent-knowledge

Knowledge base management and search tools for Wegent. Provides capabilities to list, create, update, and search knowledge bases and documents using RAG retrieval. Use this skill when the user wants to manage knowledge bases, documents, or search for information programmatically.

wecode-ai/Wegent · 51 tokens

knowledge_base

Manage the user's personal knowledge base — knowledge graph, documents, and wiki vault.

siddsachar/row-bot · 19 tokens

openlore

Query and publish to an OpenLore knowledge base over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.

aakarim/OpenLore · 42 tokens

openlore-housekeeping

Audit and maintain a shared OpenLore knowledge base. Use on a schedule or on request to find stale docs, broken links, unreviewed inbox items, and missing skill coverage, then publish an audit report.

aakarim/OpenLore · 48 tokens

continuous-learning

Use when a mistake, correction, or surprise taught the workspace something that must stick — a retro or postmortem, the same agent error corrected twice, a resolved bug's root cause, scattered notes-to-self — and route that lesson to the durable surface that fires next time. NOT a forward choice with alternatives…

ericrisco/rsc-harness · 73 tokens

Wikimate Query

A read-only search and question-answering workflow for a personal Wikimate knowledge base, made from an Obsidian note vault and a Notion index. It checks that note files really exist before using them as evidence.

sodam-ai/SoDam-WikiMate · 200 tokens