POC Agent — Agent Kits | Warp
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POC Agent
POC AgentRun
- Trigger: POC_Analysis
- Skill: Analyze active POC pilots for health
- Model: Post per-company health summaries to Slack
Overview
The POC Agent monitors every active proof-of-concept pilot in your pipeline by pulling deal data from HubSpot and querying product usage metrics from Metabase. It analyzes each company's engagement against your POC success criteria and posts a structured health summary to Slack — surfacing which pilots are on track, which are at risk, and what signals to act on.
Instead of manually cross-referencing CRM data with usage dashboards before each pipeline review, your GTM team gets a synthesized per-company brief delivered automatically to the channel where they already work.
How to deploy
Paste one prompt into Warp and the agent deploys itself:
Set up poc-bot: clone https://github.com/warpdotdev/poc-agent-oss.git if it
isn't already cloned, then run the setup skill.
The setup skill walks through the whole deployment: creating .env, collecting credentials, discovering your HubSpot and Metabase IDs via their APIs, and running read-only verification checks against each service. It is safe to re-run to finish a partial setup.
Or set it up manually:
1. Configure
Clone the repo, copy .env.example to .env, and fill in your values: HUBSPOT_ACCESS_TOKEN, the POC pipeline and stage IDs, your Metabase URL, API key, and dashboard IDs, and a Slack bot token (POC_BOT_SLACK_TOKEN) plus target channel. The README documents where to find every ID.
2. Load the environment
The scripts read from the process environment — there is no dotenv auto-loader — so export the variables before running anything:
set -a && source .env && set +a
3. Run the pipeline
# Fetch HubSpot deals + Metabase metrics
python3 .agents/skills/poc-analysis/scripts/fetch_poc_data.py
# Analyze, then post per-company health summaries to Slack
python3 .agents/skills/poc-analysis/scripts/post_to_slack.py
Once live, the agent runs on a scheduled cadence in Oz. Each run fetches fresh CRM and usage data, runs the analysis, and posts the latest health snapshot. Trigger manual runs for ad-hoc reviews or align the schedule to your pipeline review cadence.
Applications
Sales and solutions engineering teams running concurrent enterprise pilots benefit most — the agent eliminates the weekly pre-meeting data gathering that typically falls on SEs or sales ops. Every summary includes usage trends, milestone completion, and a risk signal so your team can prioritize follow-up and take targeted action before a pilot goes cold.
The agent is especially effective when POC success metrics are quantitative — active user counts, feature adoption rates, session frequency — because it can surface degradation trends days before they would otherwise appear in a manual review.
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Mac
brew install --cask warp
Linux
.deb Debian, Ubuntu .rpm Red Hat, Fedora, SUSE
Windows
.exe Windows 11/10 x64 .exe Windows 11/10 ARM64
winget install Warp.Warp