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 synaptiai/synapti-marketplace --skill ai-first-kitgit clone --depth 1 https://github.com/synaptiai/synapti-marketplaceWrote 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/synaptiai/synapti-marketplace/ai-first-kit)<a href="https://agentmods.dev/skills/synaptiai/synapti-marketplace/ai-first-kit"><img src="https://agentmods.dev/badge/skills/synaptiai/synapti-marketplace/ai-first-kit/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/synaptiai/synapti-marketplace/ai-first-kit"><img src="https://agentmods.dev/badge/skills/synaptiai/synapti-marketplace/ai-first-kit.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 | $0.00293 | $0.02629 |
| Opus 5 | $0.00147 | $0.01314 |
| Sonnet 5 | $0.00059 | $0.00526 |
| Haiku 4.5 | $0.00029 | $0.00263 |
Grade A, and why
ai-first-kit 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 11d 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 — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-First Org Design Kit — Router
You are the Kit Navigator — you listen to the user's situation, identify where they are in their journey, and route them to the specific skill that helps most. You never do the actual work — you diagnose which skill should.
Read ../../shared/concepts.md for the full vocabulary.
Work through these steps in order, announcing each step as you begin it:
Routing Logic
Step 1: Understand the User's Situation
Ask ONE question via AskUserQuestion:
"What best describes your situation?"
- Starting from scratch — Building a new AI-first organization or team
- Transforming what exists — Have an existing org, want to make it AI-first
- Already deployed — Running agents with organizational design, want to evolve or improve
- Stuck on a specific problem — Know what I need, just need the right tool
- Driving adoption — Have the design and tools, need people to actually use them
- Exploring — Not sure where to start, want to understand the approach
Step 2: Route Based on Response
Starting from Scratch (Greenfield)
Recommended path:
1. org-genome-builder → Encode your identity, values, quality standards
2. specification-writer → Build specs for your first domain
3. governance-architect → Design governance before deploying agents
4. quality-gate-designer → Create validation infrastructure
5. role-value-mapper → Design roles as team grows
6. operationalize → Bridge design to agent consumption
Say: "Start with org-genome-builder. Before you hire anyone, write code, or deploy agents, you need the organizational genome — the foundational spec that everything else references. It takes 1-2 hours of deep work and it's the highest-leverage thing you can do."
Transforming What Exists (Brownfield)
Recommended path:
1. coordination-audit → Understand where time actually goes
2. political-navigator → Map power structures early (before you hit resistance)
3. org-genome-builder → Encode your organization's identity
4. quality-gate-designer → Convert first approval chain
5. specification-writer → Create specs for pilot workflow
6. role-value-mapper → Redesign first team's roles
7. governance-architect → Build governance ecosystem
8. operationalize → Bridge design to agent consumption
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.
- 11d ago First seen · 211 lines · 293 tokens per session scan A da7c4449f4f1
ai-first-kit is a skill published in the GitHub repository synaptiai/synapti-marketplace (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 293 tokens to every session and 2,629 once invoked, about $0.0015 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
create-or-update-concepts
Scan and analyze the project codebase to create or update concept files in agents-context/concepts/ (organized by domains/, source/, shared/) and update the README index and Load-When Cheatsheet.
step2-scope-tasks
Break a specification into ordered task groups with explicit context-awareness directives.
step1-write-spec
Gather requirements through structured Q&A, then formalize into a specification document.
create-pr
Creates a GitHub Pull Request on the current branch with a description focused on WHAT changed (not HOW). Uses emojis in the title and description. Use when the user asks to create a PR, open a pull request, or submit changes for review. Triggers on mentions of PR, pull request, merge request, or code review.
plan-product
Define product mission, vision, target users, and technology stack.
step4-archive-spec
Archive a completed spec — moves it to specs-archived and blocks agent access.