DRIPCHECK

Lint email sequences and drip campaigns for deliverability: SPF/DKIM/DMARC, link health, unsubscribe presence, and CAN-SPAM/GDPR compliance.

Part of the Cognis Neural Suite.

pip install cognis-dripcheck

dripcheck scan .            # → prioritized findings in seconds

Usage — step by step

1. Install the CLI:

   pip install dripcheck

2. Lint an email sequence described in a JSON file (or - to read from stdin):

   dripcheck lint sequence.json

3. Pipe a sequence in from another step:

   cat sequence.json | dripcheck lint -

4. Read the output. Add --format json for machine-readable findings:

   dripcheck lint sequence.json --format json > drip.json

5. Wire it into CI — treat warnings as failures so deliverability regressions block release:

   dripcheck lint sequence.json --strict || exit 1

Contents

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

Why dripcheck?

A pre-send CI gate — break the build if a campaign is missing an unsubscribe link or trips a spam trigger, before it ever hits a prospect's inbox.

dripcheck 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.

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Features

• ✅ Lint Email

• ✅ Lint Sequence

• ✅ Load Sequence

• ✅ Loads Sequence

• ✅ Runs on Linux/macOS/Windows · Docker · devcontainer

• ✅ Ports in Python, JavaScript, Go, and Rust (ports/)

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Quick start

pip install cognis-dripcheck

dripcheck --version

dripcheck scan .                       # scan current project

dripcheck scan . --format json         # machine-readable

dripcheck scan . --fail-on high        # CI gate (non-zero exit)

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Example

$ dripcheck scan .

  [HIGH    ] DRI-001  example finding             (./src/app.py)

  [MEDIUM  ] DRI-002  another signal              (./config.yaml)



  2 findings · risk score 5 · 38ms

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Architecture

flowchart LR
  IN[target / export] --> P[dripcheck<br/>collect + correlate]
  P --> OUT[ranked findings]

Loading

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Use it from any AI stack

dripcheck is interoperable with every popular way of using AI:

• MCP server — dripcheck mcp (Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet)

• OpenAI-compatible / JSON — pipe dripcheck 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

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How it compares

| | Cognis dripcheck | mail-tester.com + textlint, echoing GlockApps |

|---|:---:|:---:|

| 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 mail-tester.com + textlint, echoing GlockApps, re-framed the Cognis way. Missing a credit? Open a PR.

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Integrations

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

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Install — every way, every platform

pip install "git+https://github.com/cognis-digital/dripcheck.git"    # pip (works today)

pipx install "git+https://github.com/cognis-digital/dripcheck.git"   # isolated CLI

uv tool install "git+https://github.com/cognis-digital/dripcheck.git" # uv

pip install cognis-dripcheck                                          # PyPI (when published)

docker run --rm ghcr.io/cognis-digital/dripcheck:latest --help        # Docker

brew install cognis-digital/tap/dripcheck                             # Homebrew tap

curl -fsSL https://raw.githubusercontent.com/cognis-digital/dripcheck/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/dripcheck | DEPLOY.md (AWS/Azure/GCP/k8s) |

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Related Cognis tools

• warmline — Score and rank inbound/outbound leads from a YAML rulebook, emitting a ranked queue as JSON/CSV for your SDRs and CI gates.

• 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.

• 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

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Contributing

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

⭐ If dripcheck 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 (licensing@cognis.digital). See LICENSE.

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_{Cognis Digital · one of 170+ tools in the Cognis Neural Suite · Making Tomorrow Better Today}