Render personalized cold-outreach sequences from Markdown templates + a contacts CSV, with spam-score linting and per-send dry-run preview.
Part of the Cognis Neural Suite.
pip install cognis-coldforge
coldforge scan . # → prioritized findings in seconds-
Install:
pip install -e . -
Lint a single draft (no CSV needed) with the
lintsubcommand to check a template/body for spam-trigger issues:coldforge lint --template body.txt
-
Render + lint against your contacts with the
rendersubcommand — it substitutes each contact's fields into the template and scores every resulting message:coldforge render --template body.txt --contacts contacts.csv
Add
--subject subject.txtto render a subject line too. -
Read the result. The table shows each
email, spamscore,grade, anymissingfields, and the worsttop_issue. Use--format jsonfor the full per-contact payload. Set--max-scoreto define the gate: the process exits 2 if any message exceeds it (and 3 on missing required fields under--strict):coldforge render -t body.txt -c contacts.csv --max-score 25 --format json
-
Use it in CI — block a campaign whose copy scores too spammy:
coldforge render -t body.txt -c contacts.csv --max-score 25 --format json || { echo "Message(s) over spam threshold"; exit 1; }
- Why coldforge? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing
Outreach-as-code: templates live in the repo, the spam-linter runs in CI, and you ship a sequence by merging a PR instead of clicking in a SaaS UI.
coldforge 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.
- ✅ Load Contacts
- ✅ Find Placeholders
- ✅ Missing Fields
- ✅ Render Template
- ✅ Render All
- ✅ Lint Text
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (
ports/)
pip install cognis-coldforge
coldforge --version
coldforge scan . # scan current project
coldforge scan . --format json # machine-readable
coldforge scan . --fail-on high # CI gate (non-zero exit)$ coldforge scan .
[HIGH ] COL-001 example finding (./src/app.py)
[MEDIUM ] COL-002 another signal (./config.yaml)
2 findings · risk score 5 · 38ms
flowchart LR
IN[target / manifest] --> P[coldforge<br/>checks + rules]
P --> OUT[findings (JSON / SARIF)]
coldforge is interoperable with every popular way of using AI:
- MCP server —
coldforge mcp(Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet) - OpenAI-compatible / JSON — pipe
coldforge scan . --format jsoninto 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
| Cognis coldforge | Hugo | |
|---|---|---|
| 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 Hugo/Jinja templating in the spirit of instantly.ai and lemlist, re-framed the Cognis way. Missing a credit? Open a PR.
Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (coldforge mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.
pip install "git+https://github.com/cognis-digital/coldforge.git" # pip (works today)
pipx install "git+https://github.com/cognis-digital/coldforge.git" # isolated CLI
uv tool install "git+https://github.com/cognis-digital/coldforge.git" # uv
pip install cognis-coldforge # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/coldforge:latest --help # Docker
brew install cognis-digital/tap/coldforge # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/coldforge/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/coldforge |
DEPLOY.md (AWS/Azure/GCP/k8s) |
warmline— Score and rank inbound/outbound leads from a YAML rulebook, emitting a ranked queue as JSON/CSV for your SDRs and CI gates.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
PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.
{} 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.
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 (licensing@cognis.digital). See LICENSE.