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-corpus/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-corpus)<a href="https://agentmods.dev/skills/egregore-labs/egregore/ingest-corpus"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/ingest-corpus/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-corpus"><img src="https://agentmods.dev/badge/skills/egregore-labs/egregore/ingest-corpus.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.02065 |
| Opus 5.5 | $0.00019 | $0.00826 |
| Sonnet 5.5 | $0.00010 | $0.00413 |
| Haiku 4.5 | $0.00005 | $0.00206 |
Grade A, and why
ingest-corpus 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Turn a folder of documents into a knowledge base that answers questions with its sources.
When to invoke
/ingest routes here when the user brings a body of documents to be asked questions of —
a research archive, a contract set, a manual library, a regulatory corpus. Signals: hundreds
or thousands of files, subject folders, "make this searchable", "build a knowledge base",
"I want to ask these questions".
Not this: a handful of files to keep for reference → the plain /ingest path · a meeting
recording → ingest-meeting · a Notion or Google source → those connectors.
Step 0 — Connected mode only
bash bin/config-get.sh mode
Use the printed value as {mode}; quote it in single quotes when you use it in a command, and write any single quote inside the value as '\''.
If it prints local, stop and tell the user:
This specialized corpus workflow needs Egregore Connect. It uses a hosted index of extracted statements. Your ordinary memory and search with QMD run locally.
Plain
/ingeststill works — it stores your documents and makes them searchable on this machine.
Offer egregore connect or “Not now,” then stop. Do not run the survey in Local mode. Do not describe this specialized statement index as shared hosted retrieval or hosted embeddings.
What makes this different from plain ingest
Plain ingest stores documents and makes them searchable. This additionally works out which document may answer which question, extracts the sentences that carry advice, and checks each one against the sentence it came from.
That needs a profile: which folder means which region or client, which source outranks which, and what a sentence carrying advice looks like in the language the documents are written in. Nobody can write that file cold. So it is generated from a survey plus two answers.
Step 1 — Look before asking
python3 bin/corpus_survey.py # or: python3 -c "import sys;sys.path.append('bin');import corpus_survey as cs;print(cs.summarise(cs.survey('<path>')))"
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 · +2 lines 6e3222544223
- 1mo ago First seen · 188 lines · 48 tokens per session scan A 841212363984
ingest-corpus is a skill published in the GitHub repository egregore-labs/egregore (293 stars, last pushed 9d ago), licensed MIT. It adds 48 tokens to every session and 2,065 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.
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