Borrowing it
Nothing to install: this file belongs to boettiger-lab/data-workflows. 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/boettiger-lab/data-workflows/main/.claude/skills/job-troubleshooting/SKILL.mdgit clone --depth 1 https://github.com/boettiger-lab/data-workflowsWrote 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/boettiger-lab/data-workflows/job-troubleshooting)<a href="https://agentmods.dev/skills/boettiger-lab/data-workflows/job-troubleshooting"><img src="https://agentmods.dev/badge/skills/boettiger-lab/data-workflows/job-troubleshooting.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 | $0.00088 | $0.02698 |
| Opus 5 | $0.00044 | $0.01349 |
| Sonnet 5 | $0.00018 | $0.00540 |
| Haiku 4.5 | $0.00009 | $0.00270 |
Grade A, and why
job-troubleshooting 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 8d 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.
**404 on convert → verify source URLs** with `curl -I` and directory listings (most common failure — always verify BEFORE generating YAMLs). 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.
Job Troubleshooting
Diagnose before resubmitting — a failing job re-run unchanged fails the same way.
⛔ Serialization standard: DuckDB httpfs stoi crash on oversized column chunks
The MCP can abort with SQL Error: stoi when reading GeoParquet over S3/httpfs. The root cause is a DuckDB httpfs bug on large Parquet column chunks — not the CRS tag, writer, or geometry content. Fully diagnosed in datasets #106.
What triggers it
A single Parquet column chunk in the ~2.8–2.88 GB compressed / ~3.73–3.84 GB uncompressed range causes the httpfs reader to abort with stoi. No spatial function needed — SELECT COUNT(geom) (which decodes the column) is sufficient to crash; SELECT COUNT(*) (footer only, no decode) is fine. Local file reads always work — this is exclusively an httpfs path bug.
SELECT COUNT(*) FROM read_parquet('https://…/repro-100000.parquet'); -- ✅ OK
SELECT COUNT(geom) FROM read_parquet('https://…/repro-100000.parquet'); -- ❌ stoi
The crash appears "plan-dependent" because queries that skip decoding the geometry column (e.g. filtered reads that never touch the oversized chunk) avoid it. Every individual row is valid; the data is not corrupt.
What does NOT matter
| Hypothesis | Verdict |
|---|---|
creator: geopandas |
❌ cng-convert-written file crashes identically |
OGC:CRS84 vs EPSG:4326 CRS tag |
❌ re-tagging as EPSG:4326 still crashes |
Plain DuckDB COPY re-write |
❌ still crashes |
| A single pathological geometry | ❌ local read of same file returns all rows |
Prevention (the real fix)
Keep row groups small enough that no single geometry column chunk exceeds ~1 GB compressed. For large-feature geometry (complex multipolygons, national-scale data), the default --row-group-size 100000 can pack a single chunk well past the 2.8 GB cliff. Use --row-group-size 2000 as a safe default for geometry-heavy datasets, or estimate avg(octet_length(ST_AsWKB(geom))) on a sample and size accordingly. Tracked in cng-datasets #106.
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.
- 8d ago First seen · 120 lines · 88 tokens per session scan A 1da01a89f9cb
job-troubleshooting is a skill published in the GitHub repository boettiger-lab/data-workflows (5 stars, last pushed today), licensed BSD-3-Clause. It adds 88 tokens to every session and 2,698 once invoked, about $0.0004 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 2026-08-31.
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