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 justanesta/claude-code-resources --skill customizing-vectors-rgit clone --depth 1 https://github.com/justanesta/claude-code-resourcesWrote 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/justanesta/claude-code-resources/customizing-vectors-r)<a href="https://agentmods.dev/skills/justanesta/claude-code-resources/customizing-vectors-r"><img src="https://agentmods.dev/badge/skills/justanesta/claude-code-resources/customizing-vectors-r.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 | $0.00086 | $0.00997 |
| Opus 5 | $0.00043 | $0.00498 |
| Sonnet 5 | $0.00017 | $0.00199 |
| Haiku 4.5 | $0.00009 | $0.00100 |
Grade A, and why
customizing-vectors-r 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 7d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customizing Vectors R
This skill covers type-stable operations and custom vector class design using the vctrs package.
Core Benefits
- Type stability - Predictable output types regardless of input values
- Size stability - Predictable output sizes from input sizes
- Consistent coercion rules - Single set of rules applied everywhere
- Robust class design - Proper S3 vector infrastructure
When to Use vctrs
Use vctrs when:
- Building custom vector classes - Data frame compatibility, subsetting
- Type-stable functions in packages - Guaranteed output types
- Consistent coercion/casting - Explicit rules, predictable behavior
- Size/length stability - Predictable sizing from inputs
Don't use vctrs when:
- Simple one-off analyses - Base R is sufficient
- No custom classes needed - Standard types work fine
- Performance critical + simple operations - Base R may be faster
- External API constraints - Must return base R types
vctrs vs Base R Decision Matrix
| Use Case | Base R | vctrs | When to Choose vctrs |
|---|---|---|---|
| Simple combining | c() |
vec_c() |
Need type stability, consistent rules |
| Custom classes | S3 manually | new_vctr() |
Want data frame compatibility, subsetting |
| Type conversion | as.*() |
vec_cast() |
Need explicit, safe casting |
| Finding common type | Not available | vec_ptype_common() |
Combining heterogeneous inputs |
| Size operations | length() |
vec_size() |
Working with non-vector objects |
Building Custom Vector Classes
See custom-vector-class.md for the complete pattern:
- Constructor (low-level)
- Helper (user-facing)
- Format method
Type-Stable Functions
See type-stable-functions.md for:
- Guaranteed output types with
vec_cast() - Avoiding type-depends-on-data patterns
Coercion and Casting
See coercion-casting.md for:
- Explicit casting with clear rules
- Common type finding with
vec_ptype_common() - Self-coercion methods
- Cross-type coercion methods
What ships with it
5 files 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.
- 7d ago First seen · 125 lines · 86 tokens per session scan A 714a17c972b6
customizing-vectors-r is a skill published in the GitHub repository justanesta/claude-code-resources (2 stars, last pushed 4mo ago), licensed MIT. It adds 86 tokens to every session and 997 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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