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 ScalefreeCOM/datavault4dbt-agent-skills --skill troubleshooting-datavault4dbtgit clone --depth 1 https://github.com/ScalefreeCOM/datavault4dbt-agent-skillsWrote 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/scalefreecom/datavault4dbt-agent-skills/troubleshooting-datavault4dbt)<a href="https://agentmods.dev/skills/scalefreecom/datavault4dbt-agent-skills/troubleshooting-datavault4dbt"><img src="https://agentmods.dev/badge/skills/scalefreecom/datavault4dbt-agent-skills/troubleshooting-datavault4dbt/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/scalefreecom/datavault4dbt-agent-skills/troubleshooting-datavault4dbt"><img src="https://agentmods.dev/badge/skills/scalefreecom/datavault4dbt-agent-skills/troubleshooting-datavault4dbt.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00087 | $0.01325 |
| Opus 5 | $0.00044 | $0.00662 |
| Sonnet 5 | $0.00017 | $0.00265 |
| Haiku 4.5 | $0.00009 | $0.00133 |
Grade A, and why
troubleshooting-datavault4dbt 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Troubleshooting datavault4dbt
Diagnose datavault4dbt models by symptom. The package generates the SQL, so most issues trace back to the staging metadata (hashkeys/hashdiffs), the YAML parameters, or incremental/HWM behavior.
First moves
dbt compile --select <model>and read the generated SQL intarget/— it shows exactly what the macro produced.- Enable verbose package logs: set
datavault4dbt.show_debug_logs: trueinvars:and re-run, then read the dbt.logfile. - Inspect the staging output (
dbt show --select <stage_model> --limit 20) — most raw-vault problems originate one layer up, in staging.
Symptom → cause → fix
Satellite captures too many rows (a new record every load)
- Payload doesn't match the hashdiff inputs. The satellite's
src_payloadmust be exactly the columns fed into its hashdiff in staging. If they differ, change detection misfires. - Trimming / case mismatch. Untrimmed whitespace or case differences in descriptor values change
the hashdiff each load. Check
hashdiff_use_trimandhashdiff_input_case_sensitive. - A volatile column is in the hashdiff (e.g. a load timestamp or surrogate). Remove it from the hashdiff inputs.
Satellite captures too few rows / misses changes
- A changing attribute is not in the hashdiff inputs, so the change is invisible. Add it (and to
src_payload). - For a single-attribute satellite, confirm you omitted
src_hashdiffso change detection runs directly on that one column.
Hub / link / satellite loads nothing on an incremental run
- High-water mark filtering everything out. On an incremental run the HWM only scans rows newer
than the max
ldtsalready loaded. If nothing new should load, this is correct. To rebuild, usedbt run --select <model> --full-refresh. - Multi-source entity missing
rsrc_static. Without it, the per-source max load date can't be computed and the HWM behaves unexpectedly. Addrsrc_staticper source, ordisable_hwm: true(single-source) / omitrsrc_static(multi-source) to turn the HWM off. See the staging/hubs-and-links references inusing-datavault4dbt.
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 · 97 lines · 87 tokens per session scan A 4f6ac4c2ef26
troubleshooting-datavault4dbt is a skill published in the GitHub repository ScalefreeCOM/datavault4dbt-agent-skills (22 stars, last pushed 15d ago), licensed Apache-2.0. It adds 87 tokens to every session and 1,325 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.
Other skills, from other repositories
nitpicker
Hostile audit toolkit: one entry point dispatching specialist commands — adversarial review, security, tests, docs, types, architecture, performance, reliability, caching, concurrency, error handling, resource leaks, dependencies, licensing, CI, commits, migrations, observability, API contracts, a11y, i18n, privacy…
sql-optimization-patterns
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.
tool-calling-tutor
Use when a tool-calling agent does not call a tool, sends wrong arguments, loops without stopping, or needs a function schema. Guides a four-branch diagnosis and five-step schema repair. Do not use for framework-specific, MCP-server, or production-observability questions.
dynamodb
AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.
rds
AWS RDS relational database service for managed databases. Use when provisioning databases, configuring backups, managing replicas, troubleshooting connectivity, or optimizing performance.
ecto-n1-check
Detect N+1 query anti-patterns specifically — Repo calls inside Enum/for loops, missing preloads on associations. Use when N+1 is explicitly suspected, NOT for unrelated Ecto questions or wider database performance.