Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add DataSift-Ty-Personal/SiftStack --skill sift-sequencesgit clone --depth 1 https://github.com/DataSift-Ty-Personal/SiftStackWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/datasift-ty-personal/siftstack/sift-sequences)<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/sift-sequences"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/sift-sequences/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/datasift-ty-personal/siftstack/sift-sequences"><img src="https://agentmods.dev/badge/skills/datasift-ty-personal/siftstack/sift-sequences.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00066 | $0.06996 |
| Opus 5.5 | $0.00026 | $0.02798 |
| Sonnet 5.5 | $0.00013 | $0.01399 |
| Haiku 4.5 | $0.00007 | $0.00700 |
Grade A, and why
sift-sequences scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 651 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sift Sequences
This skill both guides and helps execute sequence creation in DataSift. It is not just consultative -- it provides step-by-step UI walkthrough instructions, pre-built TCA templates verified against source code, and hands-on support for building sequences directly inside the DataSift interface.
Sequences are automations in Sift that trigger actions when specific events occur. They ensure no lead slips through the cracks by automatically creating tasks, changing statuses, moving cards, and sending notifications.
Execution Mode Detection
Before starting, detect the execution environment:
Check 1: Does scripts/manage_sequences.py exist in this skill's directory?
Check 2: Is Playwright available? Run: python -c "from playwright.sync_api import sync_playwright; print('OK')"
Check 3: Are credentials set? Check for DATASIFT_EMAIL and DATASIFT_PASSWORD in .env or environment.
Automated Mode (Claude Code CLI — all 3 checks pass)
Run sequence management directly:
# List all existing sequences
python scripts/manage_sequences.py --list
# Create the Sold Property Cleanup sequence
python scripts/manage_sequences.py --create-sold-sequence
The script handles login, navigation to /sequences, React DnD drag-and-drop (which requires slow mouse-based dragging, not Playwright's native drag), and sequence configuration. After running, proceed to the template design section below for additional sequences.
Manual Mode (Co-Work or no Playwright — any check fails)
Follow the step-by-step UI walkthrough instructions below. Claude will guide you through each drag-and-drop operation in the DataSift sequence builder.
Quick Reference
| Component | Purpose | Required |
|---|---|---|
| Trigger | Event that starts the automation | Yes |
| Condition | Additional rules that filter which records the sequence acts on | No |
| Action | What happens when triggered and conditions are met | Yes |
When to Use This Skill
What ships with it
8 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/acquisitions-sequences.md 9.6 KB
- references/board-workflows.md 5.2 KB
- references/drip-campaigns.md 6.2 KB
- references/events-overview.md 10 KB
- references/lead-management-sequences.md 9.9 KB
- references/sequence-ideation.md 6.3 KB
- scripts/datasift_core.py 16 KB runs code
- scripts/manage_sequences.py 13 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 651 lines · 66 tokens per session scan A cdded508cd66
sift-sequences is a skill published in the GitHub repository DataSift-Ty-Personal/SiftStack (23 stars, last pushed 23d ago), licensed MIT. It adds 66 tokens to every session and 6,996 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
sift-sequences compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| sift-sequencesDataSift-Ty-Personal/SiftStack | Skill | 23 | 23d ago | MIT | A | 66 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |