Borrowing it
Nothing to install: this file belongs to egregore-labs/egregore. 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/egregore-labs/egregore/main/.claude/skills/ingest/SKILL.mdgit clone --depth 1 https://github.com/egregore-labs/egregoreWrote 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/egregore-labs/egregore/ingest)<a href="https://agentmods.dev/skills/egregore-labs/egregore/ingest"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/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/egregore-labs/egregore/ingest"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 39 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 40 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 41 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 42 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 45 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00058 | $0.01110 |
| Opus 5.5 | $0.00023 | $0.00444 |
| Sonnet 5.5 | $0.00012 | $0.00222 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
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 24d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ingest
Route external material into an authorized intake plane, then promote selected evidence into curated organizational memory. Do not collapse intake and promotion.
When to invoke
Route and run organizational ingestion through Egregore Runtime for files, folders, meetings, Google Workspace, Notion, interviews, or bulk corpora. Use for 'ingest', 'bring this into Egregore', 'index this folder', or 'import our docs'.
Route
- One URL/document/reference → use the
addskill andbin/ingest-item.sh. meeting ...→ use the meeting skill.user-interview ...→ use the ingest-user-interview skill.google ...→ use the ingest-google skill.notion ...→ use the ingest-notion skill.- A large question-answering corpus or “build a knowledge base” → use the ingest-corpus skill and keep its Connected capability gate.
- No readable path →
bash bin/ingest.sh select. - File/folder/export/bulk path → use the corpus pipeline below.
- Ambiguous → ask which source class applies; do not guess a connector.
Preserve connector authorization/revocation in connector-specific Runtime adapters. This skill must not write connector lifecycle files or project state.
Invariants
- Resolve organization only from the active Egregore instance, never content or arguments.
- Keep selected/unverified bytes in gitignored local staging/quarantine.
- Canonical shared state contains admitted Markdown or reference manifests with stable ids, revisions, provenance, boundaries, errors, and tombstones.
- Register canonical state successfully before any derived retrieval refresh.
- Hard boundaries are authorization filters, never descriptive tags. Missing required boundary evidence fails closed.
- Graph projection is optional and cannot complete, block, or override intake.
- Telemetry contains structured counts/status only, never source content.
Local selection
When no path was provided:
bash bin/ingest.sh select
If cancelled, stop. If it returns a Google or Notion connector, continue in
that connector skill. Otherwise always submit the reviewed selection, using
{selection-path} for the selection path printed by the select command:
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.
- 24d ago Changed · -134 lines · +11 tokens per session 649a9ff63f54
- 1mo ago First seen · 261 lines · 47 tokens per session scan A 21eb528a5386
ingest is a skill published in the GitHub repository egregore-labs/egregore (293 stars, last pushed 9d ago), licensed MIT. It adds 58 tokens to every session and 1,110 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
mnemon
Persistent memory CLI for LLM agents. Store facts, recall past knowledge, link related memories, manage lifecycle.
durable-session-state
Persist plans, scope decisions, evidence, and reviewer/critic verdicts to durable files during long or multi-phase tasks so work survives context compaction, session resumes, and handoffs. Use for swarm-mode tasks, before context grows large, when recording approval gates, and when resuming after compaction or a…
mnemon
Persistent memory for MiniMax Code. Recall durable context, store important facts and decisions, and link related memories with the mnemon CLI.
brain-ingest
The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the brain CLI.
save-learning
Saves user instructions as persistent learnings for future sessions. Use when the user says 'remember this', 'always do X', 'from now on', 'never do Y', or gives any instruction they want persisted across sessions. Proactively suggest when the user states a preference, convention, or rule they clearly want followed in…