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 agentmods add skills/datasift-ty-personal/siftstack/sequential-presetsnpx skills add DataSift-Ty-Personal/SiftStack --skill sequential-presetsgit clone --depth 1 https://github.com/DataSift-Ty-Personal/SiftStackWhat 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 | $0.00095 | $0.03108 |
| Opus 5 | $0.00048 | $0.01554 |
| Sonnet 5 | $0.00019 | $0.00622 |
| Haiku 4.5 | $0.00010 | $0.00311 |
Grade A, and why
sequential-presets 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 2d 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 — 255 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sequential Presets Skill
This skill makes you a world-class preset consultant AND implementor. You guide users through a consultative process to design optimized sequential marketing filter presets in DataSift, then help them build each preset step-by-step in the DataSift UI.
Execution Mode Detection
Before starting, detect the execution environment:
Check 1: Does scripts/manage_presets.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 preset management directly:
# Discover all existing presets
python scripts/manage_presets.py --discover
# Add Sold exclusion to all 21 presets
python scripts/manage_presets.py --add-sold-exclusion
# Full workflow: discover + update all
python scripts/manage_presets.py --all
The script handles login, filter panel navigation, preset discovery, and Sold exclusion updates automatically using Playwright browser automation. After running, proceed to the consultative design section below.
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 click in the DataSift interface.
Core Concepts
Niche vs. Bulk Sequential Marketing
The primary distinction is the data source and marketing approach. Determine which strategy the user is employing first -- this dictates the entire preset structure.
| Aspect | Niche Sequential | Bulk Sequential |
|---|---|---|
| Data Type | First-to-market/Tier 1 (courthouse data) | Tier 2/3 (stacked lists, AI-enriched) |
| Calling Method | Manual click-to-dial | Multi-line power dialer |
| Urgency | High | Low to Medium |
| Primary Tag | Courthouse Data |
dataflik |
| Preset Count | 12 presets (00-11) | 9 presets (00-08) |
| Folder Name | 00 Niche Sequential Marketing |
01. Bulk Sequential Marketing |
What ships with it
5 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.
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.
- 2d ago First seen · 255 lines · 95 tokens per session scan A 4bcac1d29570
sequential-presets is a skill published in the GitHub repository DataSift-Ty-Personal/SiftStack (21 stars, last pushed 4d ago), licensed MIT. It adds 95 tokens to every session and 3,108 once invoked, about $0.0005 per session on Opus 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.
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