T3 Code is an app for controlling AI coding agents running on a user's computer through mobile, web, and desktop interfaces. Developers use it to work remotely with supported agents such as Codex, Claude Code, Cursor, Grok Build, OpenCode, and Antigravity. The catalogue add-ons support the T3 Code workflow.
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 pingdotgg/t3code --skill effect-developmentgit clone --depth 1 https://github.com/pingdotgg/t3codeWrote 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/pingdotgg/t3code/effect-development)<a href="https://agentmods.dev/skills/pingdotgg/t3code/effect-development"><img src="https://agentmods.dev/badge/skills/pingdotgg/t3code/effect-development/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/pingdotgg/t3code/effect-development"><img src="https://agentmods.dev/badge/skills/pingdotgg/t3code/effect-development.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 | $0.00021 | $0.00140 |
| Opus 5.5 | $0.00008 | $0.00056 |
| Sonnet 5.5 | $0.00004 | $0.00028 |
| Haiku 4.5 | $0.00002 | $0.00014 |
Grade A, and why
effect-development 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 27d 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- effect-development — 100% identical, 0 lines differ
- effect-development — 100% identical, 0 lines differ
- effect-development — 100% identical, 0 lines differ
- effect-development — 100% identical, 0 lines differ
What it actually says
Use the repository's AI documentation as targeted reference, not ambient context:
- Identify the Effect APIs and concepts involved in the change.
- Search
LLMS.mdandai-docs/srcfor those names and concepts, then read the matching sections and examples. - Apply the relevant guidance and inspect nearby source and tests for any repository-internal conventions not covered by the documentation.
The task is ready for implementation when every material Effect API or pattern has matching local guidance, or the search has established that none exists.
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.
- 27d ago First seen · 17 lines · 21 tokens per session scan A 2e674e3f30c8
effect-development is a skill published in the GitHub repository pingdotgg/t3code (27,790 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 140 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 2026-09-19.
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