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/mpaarating/ai-workflow-kit/tripnpx skills add mpaarating/ai-workflow-kit --skill tripgit clone --depth 1 https://github.com/mpaarating/ai-workflow-kitWhat 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 | $0.00013 | $0.00798 |
| Opus 5 | $0.00006 | $0.00399 |
| Sonnet 5 | $0.00003 | $0.00160 |
| Haiku 4.5 | $0.00001 | $0.00080 |
Grade A, and why
trip 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 yesterday.
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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trip
Plan trips with day-by-day itineraries, food recommendations, and logistics. Iteratively refine until it feels right.
Trigger Phrases
- "trip to [place]"
- "plan trip"
- "travel to [place]"
- "vacation to [place]"
Workflow
Step 1: Gather Basics
Extract from the user's message or ask:
- Destination
- Dates (or duration: "5 days in October")
- Travelers (solo, couple, family, group)
Step 2: Ask Preferences
Before generating the itinerary, ask about (keep it to one quick question):
- Pace: Packed schedule vs. relaxed with downtime
- Vibe: Adventure, culture, food, relaxation, nightlife, nature
- Budget: Budget-friendly, mid-range, or splurge
- Interests: Any must-dos or must-avoids
If the user already provided preferences in their initial message, skip this step.
Step 3: Generate Itinerary
Create a day-by-day plan. For each day include:
- Morning / Afternoon / Evening blocks
- Specific place names (neighborhoods, landmarks, restaurants)
- Practical notes: how to get there, estimated time, reservation tips
- One food recommendation per meal slot
Structure:
### Day 1: [Theme — e.g., "Historic Center"]
**Morning**: [Activity] — [details, location]
**Lunch**: [Restaurant/area] — [what it's known for]
**Afternoon**: [Activity]
**Dinner**: [Restaurant/area]
**Evening**: [Optional activity or downtime]
Step 4: Add Logistics Section
After the itinerary, include:
- Getting around: Best transport options (metro, rideshare, walking, rental car)
- Neighborhoods to stay in: 2-3 options with trade-offs (central vs. budget vs. vibe)
- Practical tips: Currency, tipping norms, language basics, safety notes
- Packing notes: Weather-specific or activity-specific gear
Step 5: Save
Save the complete plan.
Using {{notes}}: Create a page titled "[Destination] Trip — [Dates]" with the full itinerary.
Markdown fallback: Save to ~/.ai-workflow/trips/[destination]-[date].md.
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.
- yesterday First seen · 110 lines · 13 tokens per session scan A 1d64820bfcfd
trip is a skill published in the GitHub repository mpaarating/ai-workflow-kit (2 stars, last pushed 3mo ago), licensed MIT. It adds 13 tokens to every session and 798 once invoked, about $0.0001 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 2026-08-31.
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