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.
git clone --depth 1 https://github.com/tecton-ai/tecton-mcpWrote 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/rules/tecton-ai/tecton-mcp/tecton-optimizations)<a href="https://agentmods.dev/rules/tecton-ai/tecton-mcp/tecton-optimizations"><img src="https://agentmods.dev/badge/rules/tecton-ai/tecton-mcp/tecton-optimizations/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/rules/tecton-ai/tecton-mcp/tecton-optimizations"><img src="https://agentmods.dev/badge/rules/tecton-ai/tecton-mcp/tecton-optimizations.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 | $0.00015 | $0.00410 |
| Opus 5.5 | $0.00006 | $0.00164 |
| Sonnet 5.5 | $0.00003 | $0.00082 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
tecton-optimizations 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 2mo 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.
What it actually says
Tecton FeatureView Optimization rules
Use Tecton Aggregates Instead of Custom Aggregations When Possible
If a BatchFeatureView (BFV) uses custom aggregations, first check if they can be expressed using Tecton’s built-in Aggregate functions (listed below). If all custom aggregations can be mapped to Tecton’s Aggregate class, move them out of the transformation function and define them using Aggregate. This improves efficiency and avoids the need for incremental_materialization.
If only some aggregations can be expressed using Aggregate, factor those into a separate FeatureView.
If the aggregation cannot be expressed with Aggregate, use incremental_materialization = True.
Built-in Aggregates: approx_count_distinct(precision), approx_percentile(percentile, precision), count, first_distinct(n), first(n), last_distinct(n), last(n), max, mean, min, stddev_pop, stddev_samp, sum, var_pop, var_samp
Important: BFVs using Aggregate features should always set incremental_materialization = False for optimal backfill performance.
If you switch a custom aggregation FV to a FV that uses Aggregates and unit tests are affect you must make sure to review the rules for writing Tecton unit tests. They will help you modify the unit test.
If you switch to an Aggregation feature, you must never change the mode of the FV. Just leave it as is.
If you switch to an Aggregation feature, you MUST look at the feature engineering rules. Specifically, take a look at how you reference data sources and look for opportunities to turn a previously unfiltered data source into one that's now filtered by Tecton.
Critical: Before switching to an Aggregate feature, make sure look at examples of Tecton Aggregation features (available via tools) so you know what the right syntax looks like.
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.
- 2mo ago First seen · 31 lines · 15 tokens per session scan A ec6a5ee65280
tecton-optimizations is a cursor rule published in the GitHub repository tecton-ai/tecton-mcp (3 stars, last pushed 1y ago), licensed MIT. It adds 15 tokens to every session and 410 once invoked, about $0.0001 per session on Opus 5.5. 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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