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 text2sql-metadata-enrichmentgit 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/text2sql-metadata-enrichment)<a href="https://agentmods.dev/skills/ibm-self-serve-assets/building-blocks/text2sql-metadata-enrichment"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/text2sql-metadata-enrichment/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/text2sql-metadata-enrichment"><img src="https://agentmods.dev/badge/skills/ibm-self-serve-assets/building-blocks/text2sql-metadata-enrichment.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 Data Exfiltration · line 46 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 46 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 98 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 118 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 119 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00062 | $0.01148 |
| Opus 5 | $0.00031 | $0.00574 |
| Sonnet 5 | $0.00012 | $0.00230 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
text2sql-metadata-enrichment scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -X PUT 'https://api.ca-tor.dai.cloud.ibm.com/semantic_automation/v1/onboard_for_text_2_sql' \ How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
watsonx.data Intelligence Text2SQL Metadata Enrichment
Purpose
Expert guidance for enriching metadata in IBM watsonx.data Intelligence projects to maximise Text2SQL query accuracy. The watsonx.data Intelligence Text2SQL service uses metadata (table descriptions, column descriptions, synonyms, relationships) to understand natural language queries and generate correct SQL.
IBM Cloud Product Coverage
| IBM Cloud Product | Usage |
|---|---|
| watsonx.data Intelligence (DAI) | Text2SQL API; metadata enrichment; project/asset management |
| IBM Cloud IAM | POST /identity/token (apikey grant) |
| IBM watsonx.ai | LLM used for SQL generation (meta-llama/llama-3-3-70b-instruct default) |
Rules
- DAI base URL:
https://api.{region}.dai.cloud.ibm.com - Text2SQL endpoint:
GET /semantic_automation/v1/text_to_sql - Onboarding endpoint:
PUT /semantic_automation/v1/onboard_for_text_2_sql - Always onboard the project before importing data assets
- Metadata enrichment increases SQL accuracy significantly — always add table/column descriptions
- Supported dialects:
presto,postgresql,mssql,oracle,presto_sql,snowflake
Scope
- watsonx.data Intelligence project onboarding for Text2SQL
- Table and column metadata enrichment via DAI REST API
- Adding synonyms, business descriptions, and relationship hints
- Evaluating and improving Text2SQL query accuracy
- Feedback loop design for iterative quality improvement
Procedure
Phase 1: Onboard Project for Text2SQL
curl -X PUT 'https://api.ca-tor.dai.cloud.ibm.com/semantic_automation/v1/onboard_for_text_2_sql' \
-H 'Authorization: Bearer {TOKEN}' \
-H 'Content-Type: application/json' \
-d '{"containers": [{"container_id": "{PROJECT_ID}", "container_type": "project"}]}'
Phase 2: Import Data Assets
- Navigate to your watsonx.data Intelligence project
- Add data connection (Presto, PostgreSQL, Snowflake, etc.)
- Import specific tables as project assets
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.
- 11d ago First seen · 120 lines · 62 tokens per session scan A 37cbbfe1c91e
text2sql-metadata-enrichment is a skill published in the GitHub repository ibm-self-serve-assets/building-blocks (24 stars, last pushed yesterday), licensed Apache-2.0. It adds 62 tokens to every session and 1,148 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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