Key takeaways
- Claude agents gather context, act with tools, verify results and repeat, with permissions and hooks.
- Skills load full instructions only when relevant, and Projects keep shared knowledge and instructions.
- Subscriptions, Team seats and API credits are billed separately.
- Good agents show plans, tool calls and results so people can review them.
- Autonomy works best when bounded by limits, permissions and approval gates.
Claude can work as an agent in Claude Code, Cowork and apps built with the Claude Agent SDK, and features such as Skills and Projects shape how it handles repeated work. Usage limits, billing and credits determine how much you can do. I build AI products with several providers, such as RAG.NextUpgrad, so this page covers Claude agents, Skills, Projects, Excel, limits, billing, API credits, whether agents show their work, autonomy and a step-by-step agent flow.
How do Claude agents work?
Claude agents run a loop: gather context, take actions with tools, check results and repeat. In Claude Code, tools include reading and editing files, running commands and searching; the Claude Agent SDK lets developers build similar agents for other tasks.
Permissions control which actions need approval, and hooks let developers run checks before or after tool use. Subagents can handle parallel subtasks with separate context, returning summaries to the main agent. Project instructions in CLAUDE.md files give persistent guidance. Cowork brings this loop to non-coding work in the desktop app. Verification is part of the design: agents run tests, check outputs or ask for review before considering a task complete.
How do Claude Skills work?
Skills are folders containing a SKILL.md file with a name, description and instructions, plus optional scripts and resources. Claude sees only each skill's name and description until a task matches, then loads the full instructions and files it needs.
Also asked as: how do claude ai skills work
This progressive loading keeps context small while giving Claude specialised know-how, such as creating Word documents, following brand guidelines or running a data analysis procedure. Skills can include scripts that Claude executes in a code environment. They work across the Claude apps, Claude Code and the API, where enabled. Clear descriptions help Claude pick the right skill. Anthropic provides built-in skills for common file types, and you can write your own or share them across teams.
How do Claude Projects work?
A Project is a workspace in the Claude apps with its own knowledge files and custom instructions. Every chat inside the project can use that knowledge and follow those instructions, so you do not re-upload context each time.
Also asked as: how do claude ai projects work
Upload documents such as reports, code or guidelines to project knowledge, and write instructions describing tone, format or goals. For large knowledge bases, Claude retrieves relevant parts rather than reading everything at once. On Team and Enterprise plans, projects can be shared with colleagues, making them useful for shared workflows such as client accounts or course materials. Keep project knowledge current and remove outdated files to avoid conflicting answers.
How does Claude work in Excel?
Claude can analyse spreadsheets you upload, create and edit Excel files with formulas and charts through its file creation feature, and Anthropic has introduced a Claude add-in for Excel for some plans that works directly inside workbooks.
Also asked as: how does claude ai work in excel
Typical uses include cleaning data, building summary tables, writing formulas, explaining complex workbooks, creating financial models and generating charts. Ask Claude to explain each formula it adds, and verify calculations on sample rows, since errors in spreadsheets spread quickly. Keep a copy of the original file before edits. For sensitive financial data, check your organisation's policies before uploading. Availability of the add-in and file features depends on your plan, so check Anthropic's current documentation.
How do Claude usage limits work?
Claude usage limits cap how much you can use within rolling time windows, with some plans also having weekly limits. Usage depends on message length, attachments, conversation length, model choice and features such as Research or Claude Code.
Also asked as: how do claude limits work
Higher plans provide substantially more usage, and Claude Code shares limits with the apps on the same subscription. When you approach a limit, Claude shows when it resets. To stretch usage, start fresh chats, attach only relevant files, use Projects for shared context and pick lighter models for simple tasks. The API uses separate rate limits based on your organisation's usage tier, measured in requests and tokens per minute.
How does Claude AI billing work?
Claude app subscriptions, such as Pro and Max, bill monthly or annually through the website or mobile app stores. Team plans bill per seat, Enterprise plans use contracts, and the API bills separately for tokens used, paid through credits in the developer console.
Also asked as: how do claude ai credits work
Subscriptions and API billing are independent: a subscription does not include API usage, and API credits do not unlock app features. Manage app billing under Settings, Billing, or through your app store for mobile purchases. Some plans offer options to continue beyond usage limits with additional paid usage. Review invoices regularly, and for teams, assign seats only to active users. Check Anthropic's pricing page for current plans and terms.
How do Claude API credits work?
Claude API usage is paid from prepaid credits in Anthropic's developer console. You buy credits, and each API request deducts the cost of its input and output tokens, with optional automatic reloading when the balance runs low.
Without credits, API requests fail with billing errors, so set up reload thresholds for production applications. Usage dashboards show spending by model and workspace, helping control costs. Some startup, research and education programmes provide promotional credits. Check the console's billing terms for details such as credit expiry and invoicing options. Reduce spending with prompt caching, the Batch API for asynchronous work and smaller models for simple tasks.
Do AI agents show their work?
Well-designed agents do. They display plans, the tools they call, intermediate results and reasoning summaries, so people can follow and correct them. Coding agents show diffs and command outputs, and browser agents show what they click and type.
Transparency builds trust and catches mistakes before they cause harm. Behind the interface, traces record every model call and tool action for debugging and audits. Not all products expose this detail, and some agents summarise rather than showing every step. When choosing agent tools, prefer ones that show their work and ask for approval on important actions. When building agents, log everything and make plans visible to users.
How do AI agents work autonomously?
Agents work autonomously by running a loop without step-by-step human input: they receive a goal, decide the next action, execute tools, evaluate results and continue until success criteria are met, a limit is reached or they need help.
Also asked as: how ai agents work diagram
Autonomy can be triggered by schedules, events such as new emails, or user requests. Good designs bound autonomy with step and spending limits, permissions and approval gates for risky actions. Agents maintain state so they can resume after interruptions. Full autonomy suits low-risk, checkable tasks; high-stakes tasks keep humans in the loop. Measuring success rates on realistic tasks shows how much autonomy an agent can safely be given.
What does an AI agent workflow diagram look like?
A typical diagram flows from the user's goal into an orchestrator, which calls the language model. The model either returns a final answer or requests a tool; the tool runs, its result returns to the model, and the loop repeats until done.
Side boxes show memory and retrieval feeding context into each model call, guardrails checking actions before execution, human approval gates for risky steps, and logging capturing every step for review. Multi-agent diagrams add an orchestrator agent delegating to worker agents. Drawing your agent's diagram before building clarifies which steps are deterministic code and which need model judgement, and where failures could occur. Share the diagram with teammates to align on behaviour.
Sources
GenAI engineer and AI product builder with 2+ years shipping production-grade AI systems: RAG pipelines, fine-tuned LLMs, hybrid retrieval and multi-modal apps across vision, speech and OCR, architected end to end from ingestion to deployment. Leads engineering for SCULT INDIA's 14-member team, founded the 500+ member TechVerse Enclave community and has mentored 200+ students. Three hackathon first prizes: Changethon 2025 (IIT Roorkee), Product Genesis at Vividhotsava 2025 (CSJMU) and BYTEBATTLE (MeetKats).
Open to GenAI roles, hackathon judging, mentorship sessions and guest talks at colleges. For campus sessions the inviting institution covers the visit end to end: travel (a First AC train ticket for journeys up to five hours, a flight for anything longer), accommodation, meals, and pickup and drop; the honorarium and workshop fees are negotiable on WhatsApp or on the call, and requests are welcome from institutions that can cover the visit this way. Email pranjulrathour41@gmail.com.
