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 malloydata/publisher --skill malloy-materialization-tuninggit clone --depth 1 https://github.com/malloydata/publisherWrote 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/malloydata/publisher/malloy-materialization-tuning)<a href="https://agentmods.dev/skills/malloydata/publisher/malloy-materialization-tuning"><img src="https://agentmods.dev/badge/skills/malloydata/publisher/malloy-materialization-tuning/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/malloydata/publisher/malloy-materialization-tuning"><img src="https://agentmods.dev/badge/skills/malloydata/publisher/malloy-materialization-tuning.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 | $0.00081 | $0.01882 |
| Opus 5 | $0.00041 | $0.00941 |
| Sonnet 5 | $0.00016 | $0.00376 |
| Haiku 4.5 | $0.00008 | $0.00188 |
Grade A, and why
malloy-materialization-tuning 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 today.
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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tuning materializations for cost and performance
This skill turns the signals the open-source Publisher already records (the materialization history, per-run timings, and which sources were built vs reused) into concrete, recommendations-only advice: which sources to persist, which to stop persisting, and how to schedule and scope them. It is the local counterpart to the platform's usage-driven optimization: the Publisher has the raw signals, and you read them with the malloy-pub CLI.
Recommendations only. Never change a model, schedule, or scope without the user's explicit go-ahead. Present the findings and the proposed edits, then apply them only when asked. Persisting the wrong source wastes storage and rebuild time; unpersisting a hot one makes queries slow. Let the user decide.
Assumes the malloy-pub CLI is on PATH and points at the server (--url or MALLOY_PUBLISHER_URL, default http://localhost:4000). Substitute the real environment and package for <env> / <pkg>.
Step 1: Take inventory
Establish what the package persists today and how it is governed.
-
Persist sources: the sources annotated
#@ persist name="…"in the package's.malloyfiles. Read the models (orget_contextthe package) to list them. -
Schedule + scope:
malloy-pub schedule view --environment <env> --package <pkg>This prints the cron (or
none, meaning publish / on-demand only), the persist scope (package= artifacts reused across versions;version= per published version), and whether a freshness policy is set. A control-plane-managed package (manifestLocation set) is refreshed by the control plane, not the standalone scheduler, so leave its cadence alone.
Step 2: Read the materialization history
The history is where cost lives. Each run records its trigger, timing, and how many sources were built vs reused.
- Across the whole environment (all packages, newest first; the rows are interleaved and labeled by package, not grouped into contiguous per-package blocks):
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.
- today Changed 612cee91fa3e
- 9d ago First seen · 108 lines · 81 tokens per session scan A 6cb966f2f203
malloy-materialization-tuning is a skill published in the GitHub repository malloydata/publisher (100 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 1,882 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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