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 sparq-org/sparq --skill arrow-columnargit clone --depth 1 https://github.com/sparq-org/sparqWrote 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/sparq-org/sparq/arrow-columnar)<a href="https://agentmods.dev/skills/sparq-org/sparq/arrow-columnar"><img src="https://agentmods.dev/badge/skills/sparq-org/sparq/arrow-columnar/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/sparq-org/sparq/arrow-columnar"><img src="https://agentmods.dev/badge/skills/sparq-org/sparq/arrow-columnar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.01412 |
| Opus 5 | $0.00044 | $0.00706 |
| Sonnet 5 | $0.00018 | $0.00282 |
| Haiku 4.5 | $0.00009 | $0.00141 |
Grade A, and why
arrow-columnar 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 9d 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 — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sparq-arrow — Arrow, Parquet, IPC, and CSV interop
Use sparq-arrow when a Rust application needs a faithful columnar representation of a
sparq_engine::QueryResult. The crate maps every SELECT variable to one nullable Arrow
Struct column with five nullable UTF-8 children: kind, value, datatype,
language, and direction.
Choose a feature
- Enable
arrowforto_record_batch,from_record_batch,term_schema, andterm_struct_type. - Enable
parquetforto_parquet_bytes,from_parquet_bytes,parquet_variables_from_bytes, andparquet_row_count_from_bytes; it impliesarrow. - Enable
ipcforto_ipc_bytes,from_ipc_bytes, andipc_variables_from_bytes; it impliesarrow. - Enable
csvforto_csv_bytes,from_csv_bytes, andcsv_variables_from_bytes; it impliesarrowand adds no further dependencies (the RFC 4180 serializer and parser are hand-rolled overstd). - Leave all features disabled to retain only the dependency-free field-name constants.
All features are default-OFF. The crate is a leaf capability crate, so no Arrow
container dependency enters sparq-core, sparq-engine, or the WebAssembly bundle.
Use a RecordBatch
use sparq_arrow::{from_record_batch, to_record_batch};
let batch = to_record_batch(&result)?;
let restored = from_record_batch(&batch)?;
assert_eq!(restored.vars, result.vars);
assert_eq!(restored.rows, result.rows);
# Ok::<(), Box<dyn std::error::Error>>(())
Add the feature with cargo add sparq-arrow --features arrow.
Use Parquet bytes
use sparq_arrow::{
from_parquet_bytes, parquet_row_count_from_bytes, parquet_variables_from_bytes,
to_parquet_bytes,
};
let bytes: Vec<u8> = to_parquet_bytes(&result)?;
let variables = parquet_variables_from_bytes(&bytes)?;
let row_count = parquet_row_count_from_bytes(&bytes)?;
let restored = from_parquet_bytes(&bytes)?;
assert_eq!(variables, result.vars);
assert_eq!(row_count, result.rows.len());
assert_eq!(restored.vars, result.vars);
assert_eq!(restored.rows, result.rows);
# Ok::<(), Box<dyn std::error::Error>>(())
What ships with it
1 file 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.
- 9d ago First seen · 130 lines · 88 tokens per session scan A 1c442240af66
arrow-columnar is a skill published in the GitHub repository sparq-org/sparq (12 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 1,412 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 2026-08-31.
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