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axiom-onboarding-new-dev

axiom-onboarding-new-dev is a skill for Claude Code, Codex from Team-Deepiri/deepiri-axiom. It costs 20 tokens per session (210 once invoked), scanned A, original, Apache-2.0.

A first-week setup checklist for new developers and quality-assurance engineers joining Deepiri projects.

In plain words
What is it for?
Use it to clone the needed repositories, install the agent tools, start Docker services, check their health, and choose the right follow-up guidance for development or QA.
Why use it?
It turns an unfamiliar codebase and local environment into a defined sequence of reading documentation, starting services, and making a small first contribution.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 2repo changed 2mo ago A scan 20 tokens original Apache-2.0

Good fit Use it to clone the needed repositories, install the agent tools, start Docker services, check their health, and choose the right follow-up guidance for development or QA.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev
View source ↗ Team-Deepiri/deepiri-axiom
Install

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.

Any agent
npx skills add Team-Deepiri/deepiri-axiom --skill axiom-onboarding-new-dev
Clone the repo
git clone --depth 1 https://github.com/Team-Deepiri/deepiri-axiom

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for axiom-onboarding-new-dev

README.md
[![agentmods](https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev/github.svg)](https://agentmods.dev/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev)
Your own site
<a href="https://agentmods.dev/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev"><img src="https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev/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.

agentmods 80×15 button for axiom-onboarding-new-dev

Your own site · 80×15
<a href="https://agentmods.dev/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev"><img src="https://agentmods.dev/badge/skills/team-deepiri/deepiri-axiom/axiom-onboarding-new-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 210 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00020 $0.00210
Opus 5.5 $0.00008 $0.00084
Sonnet 5.5 $0.00004 $0.00042
Haiku 4.5 $0.00002 $0.00021

Measured 2mo ago against content hash 0610b489fdca, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

axiom-onboarding-new-dev 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 2mo 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.

skills/axiom-onboarding-new-dev/SKILL.md · 17 lines

What it actually says

Axiom Onboarding New Dev

Use when onboarding a new dev or QA engineer, or when asked "how do I get set up."

Order

  1. Clone deepiri-control-plane (local/lab) or deepiri-platform (cloud portal) and relevant service repos; ./setup.sh from deepiri-axiom for agent/skill install.
  2. Read docs/DOCUMENTATION_INDEX.md and docs/architecture/SYSTEM_ARCHITECTURE.md before touching code.
  3. Bring up the local Docker environment and confirm all containers report healthy.
  4. Take a small, well-scoped first PR or QA review — not an open-ended "look around" task.

Point new QA engineers specifically at the deepiri-qa-workflow skill; point new devs at axiom-writing-plans and axiom-tdd.

Changes

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.

  1. 2mo ago Changed 0610b489fdca
  2. 2mo ago First seen · 17 lines · 20 tokens per session scan A 003e3c3d0fe0

Subscribe to this mod's changes

axiom-onboarding-new-dev is a skill published in the GitHub repository Team-Deepiri/deepiri-axiom (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 20 tokens to every session and 210 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 2026-08-31.

Learning and teaching
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