Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Abilityai/corneliusnpx agentmods add skills/abilityai/cornelius/ref-ingestWrote 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/abilityai/cornelius/ref-ingest)<a href="https://agentmods.dev/skills/abilityai/cornelius/ref-ingest"><img src="https://agentmods.dev/badge/skills/abilityai/cornelius/ref-ingest.svg" alt="Measured on agentmods" 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 | $0.00128 | $0.02407 |
| Opus 5 | $0.00064 | $0.01203 |
| Sonnet 5 | $0.00026 | $0.00481 |
| Haiku 4.5 | $0.00013 | $0.00241 |
Grade A, and why
ref-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 3d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ref Ingest
ℹ️ First, set expectations: before anything else, print one short line with this skill's version and its most recent change — the top entry of
metadata.changelogabove — e.g.ref-ingest v1.0 — recent: initial version. Then proceed.
The one operation every input funnels through for a reference scope: incoming info → resolve → reconcile → upsert. It grows the manual single-upsert manage-reference-data with the two load-bearing hard parts — entity resolution (is this new "Reply" the existing Reply.io?) and reconciliation (new fact contradicts old → overwrite / supersede-with-history / flag) — plus the automation split by scope.
Read first (authoritative — this skill enforces, does not restate):
resources/layered-brains/COMPANY-BRAIN-SCHEMA.md→ "The update model", "The two axes" (sub-scope routing +type:/relationship:enums), "Automation boundary — split by scope".resources/layered-brains/REFERENCE-SCOPE-SCHEMA.md→ the reference-kind frontmatter contract..claude/skills/manage-reference-data/SKILL.md→ the seed upsert (Step 0 scope check + the frontmatter template). This skill is its richer successor; it does not duplicate the contract.
Composes
/ref-supersede— when reconciliation finds a validity transition that needs a prior snapshot (contract renewal, role/price change), hand off instead of overwriting. Never invoked on the market/autonomous branch (see the invariant).
State Dependencies
| Source | Location | Read | Write | Description |
|---|---|---|---|---|
| Company family | Brain/Company/{people,orgs,products,engagements,market}/*.md |
✓ | ✓ | Entity notes (one note = one entity) |
| Scope registry | resources/local-brain-search/memory_config.py |
✓ | Confirm reference-kind | |
| LBS index | resources/local-brain-search/data/ |
✓ | ✓ (reindex) | FAISS + graph; reindexed after a write |
| Search wrappers | resources/local-brain-search/run_search.sh |
✓ | Entity-resolution search under a core,Company mount |
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.
- 3d ago First seen · 136 lines · 128 tokens per session scan A c312b89ee5d3
ref-ingest is a skill published in the GitHub repository Abilityai/cornelius (106 stars, last pushed 14d ago), licensed MIT. It adds 128 tokens to every session and 2,407 once invoked, about $0.0006 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 2026-09-03.
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