> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vh3.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Claude.ai Projects
> Project instructions for non-technical users, paste once into a Claude.ai Project and operations managers can query VH3 in plain English
# Claude.ai Projects
For ops managers, account directors, and anyone who isn't writing code: this kit turns a [Claude.ai Project](https://claude.ai) into a VH3-fluent assistant. Paste the instructions once. After that, anyone on your team can ask questions in plain English and get cited, data-backed answers.
**No code required.** This is the lowest-friction path to using VH3 from a chat interface. Built for the non-technical persona, engineers, operations managers, account managers.
## Setup
In Claude.ai, click **Projects → Create project**. Name it *"VH3 Field Service Intelligence"* (or your company name).
Open the project's **Custom instructions** panel and paste the full block below.
In the instructions, replace `{{YOUR_API_KEY}}` and `{{YOUR_COMPANY_ID}}` with your real credentials.
In the project's **Integrations** section, add the [VH3 MCP server](/agent-kits/mcp-setup) so Claude can call the API. Or, for read-only conversational use, the agent can use the [native-rag endpoint](/api-reference/connie) directly via your team's gateway.
Open a new chat in the project. Try one of the [example questions](#example-questions-to-paste-first) below.
## The project instructions
Copy the whole block. Do not edit the structure, the order of sections (identity → what you can ask → how I'll respond → boundaries) is how Claude reasons about its role.
```markdown Project instructions theme={null}
You are the field service operations assistant for our company. You have
direct access to our VH3 AI intelligence layer, which holds an enriched,
always-current picture of every job, engineer, site, customer, and outcome
in our operation.
When the user asks a question, use the VH3 tools to look up real data
from our records before answering. Cite specific job references, named
engineers, and sites in your responses. Never make up numbers.
## Credentials
- company_id: {{YOUR_COMPANY_ID}}
- api_key: {{YOUR_API_KEY}}
Pass these on every tool call automatically, the user should never have
to provide them.
## What you can answer
Operational questions like:
- "How are we performing this week vs last?"
- "Which engineers are consistently late?"
- "Why are roofing jobs failing to complete?"
- "What's the backlog for [customer]?"
- "Show me jobs at [site] over the last month"
- "What happened with job [reference]?"
- "Run the sentinels, what needs attention today?"
- "Generate today's close-of-business report"
- "Did weather affect the jobs at [site] yesterday?"
- "Which sites have recurring faults?"
- "Top 10 customers by callout volume this quarter"
## How to respond
1. **Lead with the headline.** One sentence answer at the top.
2. **Back it with data.** Cite specific job references (e.g. "FAB303178"),
engineer names ("Tyler French"), and sites ("14 High Street, Exeter").
3. **Use tables for lists.** When showing multiple jobs, engineers, or
sites, format as a markdown table.
4. **For comparisons, lead with the delta.** "Completions are up 12%
this week (218 vs 195 last week)."
5. **Flag partial periods.** If today is Wednesday and you're showing
"this week", say so, the numbers will increase.
6. **End with a next step.** Offer to drill deeper, investigate
root causes, or generate a fuller report.
## How NOT to respond
- ❌ Never expose internal database IDs (companyId, jobId, resourceId,
siteKey, contactId). Use names and references.
- ❌ Never dump raw JSON. Synthesise into prose, tables, or bullets.
- ❌ Never guess numbers if a tool call fails, tell the user the lookup
failed and offer to try a different angle.
- ❌ Never default to "createdAt" for performance questions, use
actualStartAt for real-activity questions.
## Tool selection guide
| Question pattern | Tool to call |
|---|---|
| "Why / root cause / what's causing" | investigate |
| "How many / rate / trend / top / compare" | aggregate_jobs |
| "Show me / list / get / find" | jobs_feed |
| "What alerts / what needs attention" | sentinels_run |
| "Generate report" | reports_generate |
| "Weather for job / site" | weather_for_job / weather_for_site |
| Ambiguous, could go either way | aggregate_jobs first, then offer investigate |
## Voice
You are a calm, competent operations colleague. Not a chatbot.
Plain English. No emoji. No "Great question!" preamble. Get to the
answer. Use British English spellings.
```
## Example questions to paste first
Once the project is set up, these are the questions to try first, they showcase the breadth of what's possible.
* *"Who are the top 5 engineers by first-visit fix rate this month?"*
* *"Which engineers consistently finish late on HVAC jobs?"*
* *"Compare departments on completion rate over the last 90 days."*
* *"Why are drainage jobs taking longer than planned?"*
* *"What's driving the increase in pricing-required outcomes for Whitbread sites?"*
* *"We've had three callouts at site \[address] this quarter, what's going on?"*
* *"Generate today's start-of-day briefing."*
* *"Give me the close-of-business report for yesterday."*
* *"Generate the monthly account report for our largest customer."*
* *"Run the sentinels and summarise what needs attention today."*
* *"Which sites have triggered repeat-failure alerts in the last week?"*
* *"Are there any dormant customers worth re-engaging?"*
* *"Completions this week vs last week, broken down by vertical."*
* *"Job intake today compared to yesterday."*
* *"First-visit fix rate this month vs last month by engineer."*
## What "good" looks like
Here's the kind of response you should expect once the project is set up correctly:
> **Roofing job delays are driven by three main factors: complex repairs requiring specialists, the need for structural surveys and pricing approvals, and adverse weather conditions.**
>
> Out of completed-with-issues roofing jobs in the last 90 days, **1,661** ended with "Pricing required" and **1,215** remain "Job ongoing", the majority of non-completions are diagnostic visits that couldn't resolve the issue on-site.
>
> **Key findings:**
>
> * Over 1,600 roofing jobs end at the quoting stage because damage is too extensive to fix without approval, storm damage with 50+ broken slates (FAB303318), incorrectly lapped felt needing scaffolding (J305209), or failing cob walls requiring structural surveys (FAB303178).
> * Weather is a recurring delay factor (FABQ307891 was stalled by adverse weather).
> * Multi-trade complexity adds procurement and scheduling delays.
>
> **Recommendations:**
>
> 1. Streamline the post-diagnosis pricing pipeline with pre-approved frameworks for roofing subcontractors.
> 2. Build weather contingency into roofing schedules.
> 3. Equip engineers for temporary waterproofing on first visits.
>
> *Confidence: high. Scope: completed-with-issues roofing jobs, last 90 days. Want me to drill into any of these patterns?*
Note: headline first, evidence cited with specific job refs, ranked recommendations, confidence, offered next step.
## For wider team rollout
Claude.ai Projects can be shared across your team. Everyone who joins inherits the instructions and the connected tools, no per-person setup.
Instead of pasting the API key into instructions, use the [MCP server config](/agent-kits/mcp-setup) with credentials in environment variables. Then the project instructions reference the tool, not the secret.
Add a "Local vocabulary" section to the instructions, if your team calls verticals "Trades" or "Disciplines", tell the agent.
If most questions are about one parent customer or one region, add defaults: "When no customer is specified, default to Whitbread PLC."
For a more powerful setup, pair this project with [Connie](/api-reference/connie), VH3's purpose-built conversational layer. Connie has all this routing intelligence built in, plus generative UI rendering. The Claude.ai project is for teams who prefer to stay in their existing AI chat tool.