Using an agent in AgentSpot

Last updated: June 18, 2026

Learn how to use an agent, ask it good questions, read the answer carefully, and know when to trust it.

Find the right agent

  1. On the AgentSpot home page, browse the available agents.

  2. Open an agent you want to try and read these before asking anything:

    • Description — one-line summary.

    • Apps connected — the connectors it is configured to use.

To see if it is right agent for you, ask the agent itself.

Start a conversation

  1. From the detail page, click in the chat box and ask your question.

  2. Ask follow-up questions in the same conversation. (The agent remembers earlier messages)

  3. (Optional) upload a file to use with your questions, by clicking the plus button in the chat box.

Ask good questions

The single biggest factor in answer quality is your question.

Be specific. Vague questions get vague answers.

  • Weak: "How are we doing?"

  • Strong: "Compare EMEA pipeline coverage for closed-won deals in Q1 2026 vs Q2 2026, by segment."

Name the timeframe. Most data changes over time.

  • Weak: "What’s our churn?"

  • Strong: "What was monthly logo churn for the last 6 months?"

Name the slice. Region, segment, team, product, owner — whatever filter matters.

  • Weak: "Show top accounts."

  • Strong: "Show top 10 enterprise accounts in NA by ARR for FY26."

Ask one thing at a time. Two questions get better answers than one combined question.

Iterate. Treat the first answer as a starting point. Use follow-ups: "now break that down by region," "same question but only last quarter," "why did that change?"

Read the answer

A good answer has three parts. Check all three before acting.

  1. The answer itself. If the agent hedges ("approximately," "based on partial data," "I don’t have enough information"), take the hedge seriously.

  2. The sources. If you see a citation, click it and verify the source exists and looks right. If a factual answer has no citation, ask explicitly: "What source did you use?"

  3. Scope. Confirm the answer is inside the agent’s stated What it can do list. Out-of-scope answers may be guesses.

Use the answer

At the bottom of the answer, you can do the following:

  • Copy the answer into a doc, email, or message, by clicking the copy button.

  • Give Feedback with thumbs-up thumbs up or thumbs-down thumbs down. The feedback is sent to the agent’s owner and is the fastest way to improve the agent.

When an answer looks wrong

Incorrect answers can happen. Run this checklist before assuming the data is broken.

  1. Re-read your question. Was it specific? Did it name timeframe and slice?

  2. Check scope. Is what you asked inside What it can do?

  3. Check the source. Click the citation. Does the source actually contain what the answer claims?

  4. Ask the agent to explain. "Walk me through how you got that number." or "Which rows did you use?"

  5. Try a different angle. If the same question rephrased gets a very different answer, that’s a signal the agent is uncertain.

  6. Report it. Thumbs-down with a one-line note. Contact the owner for anything urgent.

Do not act on a number you can’t verify against a source.

Privacy and trust

  • Your conversations are logged. Admins can see who used which agent and when. They cannot see conversation content unless your organization has explicitly enabled that.

  • Do not paste secrets. Passwords, API keys, and credentials don’t belong in chat.

  • Treat answers as drafts. For anything material — money, customers, legal, people — verify in the source system before acting.

  • Agents can be wrong. The model can sound confident and still be incorrect, especially for out-of-scope questions.

Troubleshooting

Symptom What to try

"I don’t have access to that data."

The data isn’t attached to this agent. Check Data sources on the detail page; contact the owner if you think it should be.

The agent refuses your question.

Likely outside the agent’s scope. Check What it can’t do; contact the owner if the refusal looks wrong.

Citation links to something you can’t open.

You may not have access to that source. Ask the owner or your admin.

Different answers to the same question on different days.

Underlying data has changed. Ask the agent: "What’s the as-of date of this answer?"

The agent seems slow.

Long answers and complex questions take longer. A more specific question usually responds faster and better.

You can’t find an agent you used before.

It may have been unpublished or moved to a different group. Contact the owner, or your admin.

Get help

  • Wrong answer or missing data on this agent: contact the Owner on the detail page.

  • Can’t sign in, can’t see any agents: contact your AgentSpot admin.

  • General how-to: re-read What it can do on the detail page — most usage questions are answered there.

Managing Connectors

Connectors are the bridge between AgentSpot and your enterprise data. You have a central management hub to handle these integrations.

  • Viewing Connections: Access your personal setup to see which apps (e.g., Google Workspace, GitHub, Jira, HubSpot) you are currently logged into.

  • Adding Connections: Your administrator defines which apps are approved for your enterprise. If an app is approved but not yet active for you, click "Add Connection" to authenticate.

  • Many-to-many relationship: Connectors are global to your account. Once connected, they can be utilized by any agent that requires that specific app context.

  • On-the-fly connectivity: If you launch an agent that requires a connector you haven’t set up yet, AgentSpot will prompt you to connect right within the chat interface.

Skills: Transversal Instructions

A Skill is a repeatable set of instructions that can be applied to multiple agents.

  • What it does: Instead of repeating complex instructions in every agent, you create a Skill (e.g., "Public API Specialist" or "Slide Builder").

  • The "When" Logic: Each skill includes a description of when the agent should invoke it, helping the AI understand which specialized task it is facing.

  • Sharing & Privacy: To keep things simple, skills are either Private (only for you) or Global (available to the org). This avoids complex group-dependency issues.

Memory: Personalizing the Experience

While Instructions reside within an agent and Skills focus on tasks, Memory is personalized to you.

Memory shapes how all agents across the platform interact with you based on your preferences:

  • Format Preferences: e.g., "Always use the metric system."

  • Persona/Mindset: e.g., "Always answer through the lens of a Product Manager."

  • Tone & Style: e.g., "Maintain a friendly, casual tone" or "Be strictly professional and concise."

Memory is the "DNA" of your user experience. It ensures that every agent you interact with—regardless of its specific function—understands how you prefer to work.
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