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 LegendApp/legend-skills --skill legend-list-best-practicesgit clone --depth 1 https://github.com/LegendApp/legend-skillsWrote 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/legendapp/legend-skills/legend-list-best-practices)<a href="https://agentmods.dev/skills/legendapp/legend-skills/legend-list-best-practices"><img src="https://agentmods.dev/badge/skills/legendapp/legend-skills/legend-list-best-practices/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/legendapp/legend-skills/legend-list-best-practices"><img src="https://agentmods.dev/badge/skills/legendapp/legend-skills/legend-list-best-practices.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk 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 | $0.00069 | $0.02322 |
| Opus 5 | $0.00034 | $0.01161 |
| Sonnet 5 | $0.00014 | $0.00464 |
| Haiku 4.5 | $0.00007 | $0.00232 |
Grade A, and why
legend-list-best-practices 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 12d 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Legend List Best Practices
Apply Legend List-specific contracts, not generic prop tuning. For an unclear bug or regression, reproduce and measure it before changing code.
Surface And Workflow
- Check the installed version, platform, import, nearby usage, source, and tests. Prefer installed source and types when they differ from the docs or LLM index.
- Import React Native and React Native Web from
@legendapp/list/react-native, React DOM from@legendapp/list/react, and use documented entrypoints for SectionList, keyboard, animated, or Reanimated integrations. - Use either
dataplusrenderItemor children mode; never mix them. - Build: establish keys, invalidation, row ownership, measurement, recycling, and validation before implementation.
- Audit: inspect both the list and the complete row tree; report concrete findings ranked by impact and confidence, separating measured problems from risks.
- Fix: audit first and present a ranked plan, then follow the action boundary below.
Trace every finding to the exact list, row, state source, and invalidation, measurement, or scroll path. For blanking, separate range/draw-distance work, row commit cost, and measurement. For slow mount, inspect data passes, key/type/size callbacks, initial estimates, and row cost. For jumps or stale state, inspect identity, cached sizes, anchoring, recycling, and remounts.
Doing Vs. Suggesting
- Suggest every evidence-backed improvement, including sweeping architecture, only when the user asks to audit or improve the list. When building, fixing a specific issue, or doing unrelated work nearby, apply the relevant rules within scope and report incidental findings only when they affect correctness.
- Implement only requested and approved scope. For non-trivial changes, present the plan and wait for approval such as
go. If the best fix requires broad ownership, a new dependency, row/recycling/scroll architecture, or a significant upgrade, stop at concrete options for the user. - Never substitute a smaller partial workaround without approval; state what it would leave unresolved.
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.
- 12d ago First seen · 93 lines · 69 tokens per session scan A d9d1ac22598d
legend-list-best-practices is a skill published in the GitHub repository LegendApp/legend-skills (39 stars, last pushed 1mo ago), licensed MIT. It adds 69 tokens to every session and 2,322 once invoked, about $0.0003 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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