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 decodingai-magazine/building-a-coding-agent-from-scratch-course --skill kitaru-importer-buildergit clone --depth 1 https://github.com/decodingai-magazine/building-a-coding-agent-from-scratch-courseWrote 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/decodingai-magazine/building-a-coding-agent-from-scratch-course/kitaru-importer-builder)<a href="https://agentmods.dev/skills/decodingai-magazine/building-a-coding-agent-from-scratch-course/kitaru-importer-builder"><img src="https://agentmods.dev/badge/skills/decodingai-magazine/building-a-coding-agent-from-scratch-course/kitaru-importer-builder/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/decodingai-magazine/building-a-coding-agent-from-scratch-course/kitaru-importer-builder"><img src="https://agentmods.dev/badge/skills/decodingai-magazine/building-a-coding-agent-from-scratch-course/kitaru-importer-builder.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 | $0.00096 | $0.02781 |
| Opus 5 | $0.00048 | $0.01391 |
| Sonnet 5 | $0.00019 | $0.00556 |
| Haiku 4.5 | $0.00010 | $0.00278 |
Grade A, and why
kitaru-importer-builder 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 2d 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
1 near-identical copy found in the catalogue:
- kitaru-importer-builder — 100% identical, 32 lines differ
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kitaru importer builder
Turn a representative provider export into a locally validated Kitaru importer. Keep the path from source evidence to normalized sessions explicit so the user can see what is preserved, approximated, or unavailable.
Finish locally by default. Register code or upload trace data only when the user asks and approves each action separately.
Core contract
- Treat the installed Kitaru version and its offline schema as authoritative. Use repository examples as patterns, not proof that a command or field is installed.
- Treat trace content as sensitive. Keep raw exports out of version control and redact fixtures before writing them into the target repository.
- Keep export acquisition outside the importer. The parser consumes static bytes and parameters without network calls, filesystem writes, subprocesses, or credential reads.
- Map the source before writing code. Record accepted payload shapes, identity, hierarchy, ordering, node fields, status, completeness, and intentionally unsupported data.
- Prefer a private, single-file script importer. Use a package only when the user already has a distribution reason and the worker can install one exact pinned version.
- Preserve useful incomplete evidence. Distinguish an unreadable payload, an invalid item, and a valid but incomplete session.
- Join traces conservatively. A common key is insufficient without source-instance scope and meaningful turn order.
- Do not overwrite an existing importer file, register executable code, upload trace data, or retry a partial import without an explicit checkpoint.
- Ask separately before installing the exact importer dependencies and before running a local importer test.
- Run any untrusted or newly generated importer, including code created in the current task, only in a credential-free isolated environment. Stop if that isolation is unavailable.
- Treat local importer testing as code execution in a bounded child process, not as a security sandbox.
- Offer packaging or upstream contribution only after local success. Do not make either a completion requirement.
- Run every Kitaru CLI command and SDK script with
KITARU_ACTIVE_SKILL=kitaru-importer-builderset so the server attributes the resulting activity to this skill. - Start or restart a user-controlled worker with
--concurrency 10. UseKITARU_WORKER_CONCURRENCY=10only when the launch surface exposes worker settings through environment variables instead of CLI options.
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.
- 2d ago First seen · 182 lines · 96 tokens per session scan A b302208374f8
kitaru-importer-builder is a skill published in the GitHub repository decodingai-magazine/building-a-coding-agent-from-scratch-course (383 stars, last pushed 2d ago), licensed Apache-2.0. It adds 96 tokens to every session and 2,781 once invoked, about $0.0005 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 2026-09-09.
Other skills, from other repositories
can
A debugging tool for CAN and CAN-FD, communication systems used by vehicles and embedded devices. It can find interfaces, monitor and send messages, record logs, decode DBC database files, and report bus statistics.
telnyx-ai-inference-curl
Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides REST API (curl) examples.
spring-ai-integration
Use when integrating LLMs, chat clients, embeddings, RAG pipelines, or AI agents into Spring Boot. Covers Spring AI ChatClient, prompt templates, embeddings, vector stores, and structured output. Use when user mentions Spring AI, LLM, ChatGPT, Claude, RAG, embeddings.
telnyx-stt-python
Transcribe audio to text via the OpenAI-compatible transcription endpoint. Supports multiple models, languages, and keyword biasing. Also lists available speech-to-text providers and service types.
meta-prompting
Structured decision modifiers (/think, /verify, /adversarial, /edge, /confidence, /assumptions, etc.) to stress-test conclusions, evidence, assumptions, alternatives, and edge cases. Use when validating an important design, architecture decision, or ambiguous plan before committing.
ai-engineer
Expert knowledge in AI/ML development, model deployment, and MLOps practices.