Borrowing it
Nothing to install: this file belongs to JStaRFilms/deprecated-Takomi_Code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/JStaRFilms/deprecated-Takomi_Code/master/.agent/skills/convex-component-authoring/SKILL.mdgit clone --depth 1 https://github.com/JStaRFilms/deprecated-Takomi_CodeWrote 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/jstarfilms/deprecated-takomi_code/convex-component-authoring)<a href="https://agentmods.dev/skills/jstarfilms/deprecated-takomi_code/convex-component-authoring"><img src="https://agentmods.dev/badge/skills/jstarfilms/deprecated-takomi_code/convex-component-authoring/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/jstarfilms/deprecated-takomi_code/convex-component-authoring"><img src="https://agentmods.dev/badge/skills/jstarfilms/deprecated-takomi_code/convex-component-authoring.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 | $0.00028 | $0.02643 |
| Opus 5 | $0.00014 | $0.01321 |
| Sonnet 5 | $0.00006 | $0.00529 |
| Haiku 4.5 | $0.00003 | $0.00264 |
Grade A, and why
convex-component-authoring 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 9d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
3 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.
- 9d ago First seen · 458 lines · 28 tokens per session scan A 561346aded09
convex-component-authoring is a skill published in the GitHub repository JStaRFilms/deprecated-Takomi_Code (3 stars, last pushed 5mo ago), with no licence file. It adds 28 tokens to every session and 2,643 once invoked, about $0.0001 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.
Other skills, from other repositories
convex-component-authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management.
convex-component-authoring
How to create, structure, and publish self-contained Convex components with proper isolation, exports, and dependency management.
tauri-django-react
Agents should invoke this skill for Tauri + Django + React desktop apps, especially backend lifecycle, CORS/auth, frontend integration, mandatory light/dark theming, German/English i18n, build packaging, dual desktop/web deployment, Rust commands, and platform-specific gotchas.
shoo-auth
Use when evaluating, implementing, reviewing, or debugging Shoo auth (shoo.dev) Google sign-in in browser apps, including @shoojs/react, @shoojs/auth, hosted shoo.js, Convex custom JWT integration, PKCE callbacks, session checks, and server-side idtoken verification. Do not use for unrelated auth systems.
frontend-design
Use when building a new web interface or reshaping an existing one. Guides distinctive visual direction, typography, layout, motion, and interface copy without falling back to templated AI design.
frontend-developer
Becomes a senior frontend developer who builds accessible, performant user interfaces with modern web technologies. Use when the user needs UI components, responsive layouts, accessibility improvements, or frontend performance optimization. Do NOT use when designing backend APIs, configuring server infrastructure, or…