Clari Hello World

VerifiedCaution

Export your first Clari forecast and pipeline snapshot. Use when testing Clari API connectivity, pulling forecast data, or learning the export API structure.

Sby Skills Guide Bot
DevelopmentBeginner
7/23/2026
Claude Code
#clari#api-integration#forecast-export#saas#revenue-intelligence

Recommended for

Automated summary

Makes the first calls to the Clari Export API: list available forecasts, kick off a forecast snapshot export, and poll job status until the data is downloaded.

Strengths

  • Complete four-step walkthrough with copy-pasteable curl and Python snippets
  • Covers job status polling and downloading/parsing the resulting export file
  • Common error table (401, unknown forecast name, pending job) with concrete fixes
  • Starts by listing forecasts so you get the exact name the export endpoint expects

Limitations

  • Assumes a valid CLARI_API_KEY and at least one forecast already configured in Clari
  • Does not cover initial auth setup, which is deferred to the clari-install-auth skill
  • The polling loop is blocking with no timeout or backoff
When to use it

Use it to validate Clari API connectivity or quickly prototype a forecast and quota data export.

When not to use it

Avoid it when you need scheduled recurring exports or data transformation beyond a raw download.

Security analysis

Caution
Quality score86/100

This is a legitimate Clari export workflow with no destructive commands, obfuscation, or obvious secret exfiltration. Because it handles an API key and uses network-enabled shell/Python tools, it is best classified as caution rather than fully safe.

Findings
  • •Uses Bash(curl:*) and Bash(python3:*) with network access to api.clari.com and reads CLARI_API_KEY from the environment.
  • •The polling loop is unbounded (`while True`) and has no timeout or maximum retry count, so a stuck export could poll indefinitely.
  • •Step 4 downloads from a server-provided `downloadUrl` without checking HTTP status or validating the host; this is low risk for the trusted Clari API but worth noting.
How this analysis is made

Examples

Test Clari API connectivity
Run the clari hello world flow: list my available forecasts and show their IDs and time periods.
Export Q1 forecast snapshot
Export the company_forecast for 2026_Q1 from Clari including quota and CRM totals, then poll the job and print the download URL.
Parse exported forecast data
Download the completed Clari export job and print a per-rep summary of forecast amount vs quota.

name: clari-hello-world description: 'Export your first Clari forecast and pipeline snapshot.

Use when testing Clari API connectivity, pulling forecast data,

or learning the export API structure.

Trigger with phrases like "clari hello world", "clari first export",

"clari test api", "clari forecast export".

' allowed-tools: Read, Write, Edit, Bash(curl:), Bash(python3:) version: 1.6.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags:

  • saas
  • revenue-intelligence
  • forecasting
  • clari compatibility: Designed for Claude Code

Clari Hello World

Overview

First API calls against Clari: list available forecasts, export a forecast snapshot, and check export job status. The Clari Export API is the primary integration point for getting forecast, quota, and CRM data out of Clari.

Prerequisites

  • Completed clari-install-auth setup
  • CLARI_API_KEY environment variable set
  • At least one forecast configured in Clari

Instructions

Step 1: List Available Forecasts

curl -s -H "apikey: ${CLARI_API_KEY}" \
  https://api.clari.com/v4/export/forecast/list \
  | jq '.forecasts[] | {forecastName, forecastId, timePeriods}'

Step 2: Export a Forecast

import requests
import json
import os
import time

api_key = os.environ["CLARI_API_KEY"]
headers = {"apikey": api_key, "Content-Type": "text/plain"}

# Replace with your forecast name from Step 1
forecast_name = "company_forecast"

payload = json.dumps({
    "timePeriod": "2026_Q1",
    "typesToExport": [
        "forecast",
        "quota",
        "forecast_updated",
        "adjustment",
        "crm_total",
        "crm_closed"
    ],
    "currency": "USD",
    "schedule": "NONE",
    "includeHistorical": False,
    "exportFormat": "JSON"
})

response = requests.post(
    f"https://api.clari.com/v4/export/forecast/{forecast_name}",
    headers=headers,
    data=payload,
)
response.raise_for_status()

job = response.json()
print(f"Export job started: {job['jobId']}")
print(f"Status: {job['status']}")

Step 3: Check Export Job Status

# Poll for job completion
job_id = job["jobId"]

while True:
    status_resp = requests.get(
        f"https://api.clari.com/v4/export/jobs/{job_id}",
        headers={"apikey": api_key},
    )
    status = status_resp.json()

    if status["status"] == "COMPLETED":
        print(f"Export ready: {status['downloadUrl']}")
        break
    elif status["status"] == "FAILED":
        print(f"Export failed: {status.get('error', 'Unknown')}")
        break

    print(f"Status: {status['status']}... waiting 5s")
    time.sleep(5)

Step 4: Download and Parse Results

if status["status"] == "COMPLETED":
    download = requests.get(status["downloadUrl"])
    forecast_data = download.json()

    # Print summary
    for entry in forecast_data.get("entries", [])[:5]:
        print(f"  Rep: {entry.get('ownerName')}")
        print(f"  Forecast: ${entry.get('forecastAmount', 0):,.0f}")
        print(f"  Quota: ${entry.get('quotaAmount', 0):,.0f}")
        print()

Output

  • List of forecasts with IDs and time periods
  • Exported forecast data with rep-level calls
  • Quota, adjustments, and CRM totals

Error Handling

| Error | Cause | Solution | |-------|-------|----------| | 401 Unauthorized | Bad API key | Regenerate token in Clari settings | | No forecasts listed | Wrong org or no forecasts configured | Contact Clari admin | | Job stays PENDING | Large export | Wait longer, check job status endpoint | | 404 on forecast name | Name mismatch | Use exact name from list endpoint |

Resources

Next Steps

Proceed to clari-local-dev-loop for development workflow setup.

From the file to a first result

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View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/clari-hello-world-mrx3xywb/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/clari-hello-world-mrx3xywb' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/clari-hello-world-mrx3xywb/download' --output '.skill-downloads/clari-hello-world-mrx3xywb/SKILL.md.part' && mv '.skill-downloads/clari-hello-world-mrx3xywb/SKILL.md.part' '.skill-downloads/clari-hello-world-mrx3xywb/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Environment declared by the author: Designed for Claude Code

Tools declared by the author (check availability in your agent): Read, Write, Edit, Bash(curl:*), Bash(python3:*)

Original excerpt: Prerequisites
  • Completed clari-install-auth setup
  • CLARI_API_KEY environment variable set
  • At least one forecast configured in Clari

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/clari-hello-world-mrx3xywb/SKILL.md' && test -s '.skill-downloads/clari-hello-world-mrx3xywb/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/clari-hello-world' && cp -R '.skill-downloads/clari-hello-world-mrx3xywb' '.claude/skills/clari-hello-world'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/clari-hello-world-mrx3xywb'

openskills read 'clari-hello-world-mrx3xywb'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/clari-hello-world-mrx3xywb/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

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