Warmline

pip install cognis-warmline
warmline scan .            # → prioritized findings in seconds

🔎 Example output

Real, reproducible output from the tool — runs offline:

$ warmline-emit --version
warmline 0.1.0

$ warmline-emit --help
usage: warmline [-h] [--version] {score} ...

Git-versioned lead scoring: score & rank leads from a YAML rulebook.

positional arguments:
  {score}
    score     score leads and print a ranked queue

options:
  -h, --help  show this help message and exit
  --version   show program's version number and exit

WARMLINE CLI — score and rank leads from a YAML rulebook.

Examples:
    # Rank leads, human-readable table
    warmline score --rules rulebook.yaml --leads leads.csv

    # Emit ranked queue as JSON for piping into CI / a CRM sync
    warmline score -r rulebook.yaml -l leads.json --format json > queue.json

    # Gate: fail (exit 2) if no lead reaches the 'hot' tier
    warmline score -r rulebook.yaml -l leads.csv --min-tier hot

Exit codes:
    0  success
    1  usage / parsing error
    2  gate failure (--min-tier / --min-score not met by any lead)

Blocks above are real warmline output — reproduce them from a clone.

Sample result format (illustrative values — run on your own data for real findings):

{
"findings": [
    {
        "id": "1234567890",
        "title": "Suspicious Activity Detected",
        "description": "Anomalous network traffic observed from IP 192.168.1.100",
        "labels": ["suspicious", "network"]
    },
    {
        "id": "2345678901",
        "title": "Malware Detection",
        "description": "Malware identified on system with ID 1234567890",
        "labels": ["malware", "system"]
    }
]
}

Usage — step by step

1. Install the CLI (console script warmline):

   pip install cognis-warmline
   

2. Score & rank leads against a YAML rulebook (leads file may be .csv, .json, or .yaml):

   warmline score --rules rulebook.yaml --leads leads.csv
   

3. Read the ranked queue as JSON for a CRM sync or pipeline, and trim to the top N:

   warmline score -r rulebook.yaml -l leads.json --format json --top 25 > queue.json
   

4. Gate on a tier or score — exit 2 if no lead reaches the threshold:

   warmline score -r rulebook.yaml -l leads.csv --min-tier hot
   warmline score -r rulebook.yaml -l leads.csv --min-score 80
   

5. Automate in CI — fail the job unless at least one lead is hot:

   - run: pip install cognis-warmline
   - run: warmline score -r rulebook.yaml -l leads.csv --format json --min-tier hot
   

Contents

• Why warmline? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing

Why warmline?

A self-hostable, git-versioned lead-scoring engine — every score change is a reviewable PR diff, killing the 'why did this lead get routed here' black box.

warmline is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.

Features

• ✅ Parse Simple Yaml
• ✅ Load Rulebook
• ✅ Load Rulebook File
• ✅ Load Leads
• ✅ Load Leads File
• ✅ Score Lead
• ✅ Score Leads
• ✅ Rank
• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

Quick start

pip install cognis-warmline
warmline --version
warmline scan .                       # scan current project
warmline scan . --format json         # machine-readable
warmline scan . --fail-on high        # CI gate (non-zero exit)

Example

$ warmline scan .
  [HIGH    ] WAR-001  example finding             (./src/app.py)
  [MEDIUM  ] WAR-002  another signal              (./config.yaml)

  2 findings · risk score 5 · 38ms

Architecture

flowchart LR
  IN[input] --> P[warmline<br/>analyze + score]
  P --> OUT[report]

Use it from any AI stack

warmline is interoperable with every popular way of using AI:

• MCP server — warmline mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)
• OpenAI-compatible / JSON — pipe warmline scan . --format json into any agent or LLM
• LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
• CI / scripts — exit codes + SARIF for non-AI pipelines

How it compares

	Cognis warmline	n8n + dbt (declarative scoring) crossed with HubSpot lead scoring
Self-hostable, no account	✅	varies
Single command, zero config	✅	⚠️
JSON + SARIF for CI	✅	varies
MCP-native (AI agents)	✅	❌
Polyglot ports (JS/Go/Rust)	✅	❌
Open license	✅ COCL	varies

Built in the spirit of n8n + dbt (declarative scoring) crossed with HubSpot lead scoring, re-framed the Cognis way. Missing a credit? Open a PR.

Integrations

Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (warmline mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.

Install — every way, every platform

pip install "git+https://github.com/cognis-digital/warmline.git"    # pip (works today)
pipx install "git+https://github.com/cognis-digital/warmline.git"   # isolated CLI
uv tool install "git+https://github.com/cognis-digital/warmline.git" # uv
pip install cognis-warmline                                          # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/warmline:latest --help        # Docker
brew install cognis-digital/tap/warmline                             # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/warmline/main/install.sh | sh

Linux	macOS	Windows	Docker	Cloud
scripts/setup-linux.sh	scripts/setup-macos.sh	scripts/setup-windows.ps1	docker run ghcr.io/cognis-digital/warmline	DEPLOY.md (AWS/Azure/GCP/k8s)

Related Cognis tools

• coldforge — Render personalized cold-outreach sequences from Markdown templates + a contacts CSV, with spam-score linting and per-send dry-run preview.
• pactgen — Generate branded sales proposals and SOWs from a YAML scope file + pricing table into PDF/HTML, with a deterministic line-item math check.
• crmsync — Bidirectional, idempotent sync of contacts/deals between a local SQLite source-of-truth and CRM APIs (HubSpot/Pipedrive/Salesforce) via one config.
• dripcheck — Lint email sequences and drip campaigns for deliverability: SPF/DKIM/DMARC, link health, unsubscribe presence, and CAN-SPAM/GDPR compliance.
• dealflow — Model your sales pipeline as a YAML state machine and compute conversion rates, stage velocity, and weighted forecast straight from CRM exports.
• introbot — Find warm-intro paths through your team's combined network graph and draft double-opt-in intro requests from a single contacts manifest.

Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram

Contributing

PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.

⭐ If warmline saved you time, star it — it genuinely helps others find it.

Interoperability

{} composes with the 300+ tool Cognis suite — JSON in/out and a shared OpenAI-compatible /v1 backbone. See INTEROP.md for the suite map, composition patterns, and reference stacks.

License

Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license ([email protected]). See LICENSE.

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