Claude knows how software is generally written. It does not know your deployment checklist, your report template, your naming conventions, or which of your three databases is the authoritative one. A skill is where that knowledge lives — written once, loaded only when it is relevant, and versioned like any other code.
AGI Software Solutions builds the three things that make Claude behave like someone who has worked at your company for a year: Agent Skills — folders of instructions and scripts Claude loads only when a task calls for them; connectors — MCP servers that let Claude read and act in your own systems under scoped credentials; and Claude Code plugins that bundle skills, commands and hooks so every engineer installs one thing and gets the same setup. A focused skill typically runs $6k–$15k; a connector wired into a live system $15k–$40k.
Most teams solve this by pasting the same three paragraphs into every conversation. A skill puts that knowledge permanently within reach, costs almost nothing until it is actually needed, and gets reviewed like any other change.
Only a short description sits in context; the full instructions load when a task matches. You can ship a dozen skills without slowing down every conversation that does not need them.
Skills live in a repository with versions and history, so changing how Claude does something goes through the same review as changing anything else — and can be rolled back the same way.
Connector credentials are stored outside the conversation and attached at call time, so a connector can act in your systems without a token ever appearing in context.
A plugin installs the skills, commands and connectors as one unit, so “it works on my machine” stops being a thing people say about their AI tooling.
An Agent Skill is a folder containing a SKILL.md file — instructions written for Claude rather than for a person — alongside any scripts, templates or reference files the task needs. Only a short description sits in context by default; Claude reads the full file when the work actually calls for it. That progressive disclosure is the whole point: you can give Claude a great deal of specialist knowledge without paying for it on every request.
Skills, connectors and plugins solve three different parts of the same problem. A skill gives Claude knowledge and procedure. A connector gives it reach into your systems. A plugin packages both — plus commands and automation hooks — so a whole team installs one thing rather than following a setup document nobody keeps current.
Three words used almost interchangeably in most conversations. They are not the same thing, and most teams need more than one.
| Skill | Connector | Plugin | |
|---|---|---|---|
| What it gives Claude | Knowledge and procedure | Reach into your systems | A packaged setup |
| Built from | SKILL.md, scripts, templates | An MCP server plus scoped credentials | Skills, commands, hooks, connectors |
| Loaded | On demand, when the task matches | When the tool is called | Installed once per person or repo |
| Answers | “Do it the way we do it” | “Look it up in our system” | “Everyone gets the same setup” |
| Typical cost | $6k–$15k | $15k–$40k | $10k–$25k |
The same process across every AI Development project, scaled to the size of the problem.
We work out what the system actually has to do, what data exists, and what happens today when it goes wrong.
Architecture, model choice, integration points and failure handling, defined before any of it gets built.
Connecting to the systems that hold your data, with security and permission boundaries handled properly.
The system takes on real work, in the workflows your team already uses rather than beside them.
Tuned against real usage and measured with evals, because how people use a system is never quite how it was designed.
The patterns we see deliver, across startups, SMEs and enterprise teams.
Deployment runbooks, review checklists, architecture decisions and code style written as skills, so Claude follows them without anyone re-explaining on every task.
Skills that produce spreadsheets, decks and reports in your house template rather than a generic one — the same shape every time, from anyone on the team.
MCP connectors that let Claude query your ERP, CRM, ticketing or warehouse systems directly, scoped to what the person asking is already allowed to see.
Skills, slash commands, hooks and connectors bundled so engineers install once — and updates reach everyone the same way rather than by word of mouth.
Context-aware multi-channel chat that qualifies inbound leads and routes them to the right person.
One inbox across web chat, email, WhatsApp and Facebook, with AI replies trained on past resolutions.
Support chatbot, live SEO analyser and a vector recommendation engine, all sharing one retrieval layer.
“We needed a voice agent that could actually qualify leads, not a chatbot pretending to be one. The team shipped a sub-700ms pipeline in 6 weeks. It now handles 5k calls a day.”
“What sold us was their willingness to put AI engineers and product designers on the same call. We got working prototypes by week two and a production rollout in three months.”
“AGI designed a CRM system tailored to our client management process. It is intuitive, reliable, and has centralized all our communication and history in one dashboard. This has greatly improved client retention.”
A folder with a SKILL.md file — instructions written for Claude — plus any scripts, templates or reference files the task needs. Claude sees only a one-line description until a task matches it, then reads the full contents. In practice it is the difference between explaining your release process every time and writing it down once.
A focused skill capturing one process runs $6k–$15k. A connector into a live business system, including auth and permission scoping, runs $15k–$40k. A plugin bundling several skills and commands for a team runs $10k–$25k. A full internal setup — a handful of skills, one or two connectors and a distributed plugin — typically lands at $25k–$60k.
A connector is an MCP server, packaged and authenticated so Claude can use it. The distinction is only where the work sits: building the server is protocol engineering, and getting it into Claude with the right credentials and permission scoping is integration. We do both, and if you already have a working MCP server we will just do the second half.
No, and this is worth being precise about. Connector credentials are stored outside the conversation and attached to outbound calls, so no token appears in context where it could be logged, summarised or echoed back. Never put an API key in a prompt or a skill file — anything written there persists in the conversation history.
A first skill is usually working within 1–2 weeks, because the hard part is deciding what your process actually is rather than writing the file. Connectors run 3–6 weeks depending on the system and its auth. A team plugin comes together once the skills exist, usually in a week or two.
Skills and connectors work wherever your team uses Claude — Claude Code, the API, and agent deployments — so the same skill serves an engineer at the terminal and an automated pipeline. Plugins are the Claude Code packaging format specifically. If your team is spread across surfaces, we scope the skills first, since they are the part that travels.
Tell us what the system would need to do and what it is replacing. We will tell you whether it is worth building and roughly what it takes.