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.
npx skills add ibm-self-serve-assets/building-blocks --skill udi-opensearchgit clone --depth 1 https://github.com/ibm-self-serve-assets/building-blocksWrote 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/ibm-self-serve-assets/building-blocks/udi-opensearch)<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/udi-opensearch"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/udi-opensearch/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/ibm-self-serve-assets/building-blocks/udi-opensearch"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/udi-opensearch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Privilege Escalation · line 150 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00074 | $0.03011 |
| Opus 5 | $0.00037 | $0.01505 |
| Sonnet 5 | $0.00015 | $0.00602 |
| Haiku 4.5 | $0.00007 | $0.00301 |
Grade A, and why
udi-opensearch 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 12d 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 — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
UDI Skill — Document Ingestion into OpenSearch
This skill scaffolds a pure-Python two-part UDI pipeline:
- Part 1 —
setup.py— run once: registers COS + OpenSearch connections, creates the UDI flow, saves all IDs toudi_config.json - Part 2 —
ingest.py— run every time: readsudi_config.jsonand starts a new flow run
No Terraform required — infrastructure (COS, WML, OpenSearch) is a user prerequisite.
Skill directory layout
.bob/skills/udi-opensearch/
├── SKILL.md
├── .gitignore → .gitignore
└── scripts/
├── .env.example → scripts/.env.example (copy to scripts/.env)
├── setup.sh → scripts/setup.sh (Part 1 — run once)
├── ingest.sh → scripts/ingest.sh (Part 2 — run repeatedly)
├── setup.py → scripts/setup.py (called by setup.sh)
├── ingest.py → scripts/ingest.py (called by ingest.sh)
└── requirements.txt → scripts/requirements.txt
Pipeline overview
COS bucket → extract text (OCR) → chunk → watsonx embeddings → OpenSearch index
| # | UDI Operator | Role |
|---|---|---|
| 1 | ingest_cpd_connections |
Reads documents from COS via a registered watsonx connection |
| 2 | extract_cpd |
Extracts text with OCR (high quality mode) |
| 3 | chunker |
Splits text into overlapping chunks |
| 4 | embeddings |
Generates vector embeddings (ibm/slate-30m-english-rtrvr-v2) |
| 5 | opensearch |
Indexes chunks + vectors into an OpenSearch index |
Step 0a — Detect the host OS
Before issuing any shell commands, detect the OS:
python -c "import platform; print(platform.system())"
| OS result | Shell | Python binary | Set env var |
|---|---|---|---|
Linux or Darwin |
bash | python3 |
export KEY="val" |
Windows |
cmd / PowerShell | python |
set KEY=val (cmd) or $env:KEY="val" (PS) |
Step 0b — Prerequisites checklist
Before proceeding, confirm the user has all of the following.
Present as a checklist using ask_followup_question if anything is unclear.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 247 lines · 74 tokens per session scan A e3304ba4a665
udi-opensearch is a skill published in the GitHub repository ibm-self-serve-assets/building-blocks (24 stars, last pushed today), licensed Apache-2.0. It adds 74 tokens to every session and 3,011 once invoked, about $0.0004 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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