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Compact two-skill starter: clarify positioning and choose a lead magnet. Use Marketing Launch for the broader eight-skill go-to-market workflow.

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Build an evidence-led marketing plan from ICP and competition through positioning, campaigns, growth and measurement.

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Diagnose architecture and context, plan agent-team responsibilities, then organize project context and session handoffs. Memory and cost-runtime reviews remain outside this pack.

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Review the journey from landing page and lead capture through registration, first value and transparent upgrades.

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Plan a campaign, draft its channel content and review the work against actual brand guidance.

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Prioritize an editorial roadmap and plan how to launch and distribute it across suitable channels.

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Understand customer needs, compare competitors and plan a community around real member value.

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Choose a relevant lead magnet, then draft a permission-based nurture journey with entry, suppression and exit rules.

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Profile a dataset, choose and interpret statistical methods, then validate calculations and conclusions before sharing.

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01 · Category

What the MCP returns at this step

75 · Marketing · Ads Operations

Meta Ad Set Planning

Prepare Meta ad-set targeting, attribution and bids under a verified parent campaign. Use Meta Campaign Planning for campaign-level settings.

metaanzeigengruppenanlagemeta-create-adset

Meta Ad Set Creation · Original SKILL.md

---
name: meta-create-adset
description: "Use when creating a Meta ad set. Parent campaign verification, pixel detection, targeting patterns, attribution spec, bid amount rules, placement/optimization guardrails. Loaded after the create master skill."
---
# Meta Ads - Create Ad Set

## CRITICAL: Do NOT combine with other creation steps
Each creation step (campaign → ad set → ad+creative) has its own separate flow. The ad set step happens AFTER campaign has been created and executed.

## user_input Rules

Do NOT call `user_input` for ad set creation. Auto-detect and auto-configure ALL fields. Show a brief summary in chat, then call `facebook_propose_create_adset` directly. The user can review and edit everything in the approval UI.

**Auto-configure ALL fields silently:**

| Field | Fixed Value | Source |
|-------|------------|--------|
| `adset_name` | Auto-generate | Follow parent campaign's naming convention (e.g., "Brand \| Audience \| Date"). If no pattern, generate from campaign context + targeting. |
| `target_countries` | Auto-detect | Most common countries from Step 4. If no existing ad sets, use account's default country. |
| `daily_budget` | Auto-detect or ASK (ABO only) | Median budget from Step 4. **If no existing ad sets with budgets → ASK the user for budget.** NEVER invent a number. Skip if CBO. |
| `bid_amount` | Auto-detect or ASK (if needed) | Only if campaign uses COST_CAP or BID_CAP. Use median from existing ad sets. **If no existing bid data → ASK the user.** NEVER invent a number. |
| `campaign_id` | From prior step | Just-executed campaign's `new_campaign_id` |
| `campaign_name` | From prior step | Campaign name used during creation — UI breadcrumb only |
| `billing_event` | `IMPRESSIONS` | Fixed for Sales |
| `destination_type` | `WEBSITE` | Default for Sales |
| `optimization_goal` | `OFFSITE_CONVERSIONS` | Default for Sales — optimize for conversions. Do NOT use VALUE unless user explicitly asks AND pixel is eligible. |
| `status` | `ACTIVE` | Default — ad set goes live as soon as an active ad is attached |
| `promoted_object` | `{ pixel_id: <from Step 3>, custom_event_type: "PURCHASE" }` | Auto-detect pixel. If 1 pixel → use it. If multiple → show in chat, ask user to pick (this is the ONE exception where user input is needed). |
| `attribution_spec` | `[{ event_type: "CLICK_THROUGH", window_days: 7 }, { event_type: "VIEW_THROUGH", window_days: 1 }]` | Standard 7d click + 1d view |
| `is_campaign_cbo` | `true` if campaign has budget | From Step 2 |
| `campaign_bid_strategy` | From Step 2 | `facebook_get_campaign_details` → bid_strategy |
| `bid_strategy` | Do NOT set | Inherits from campaign |
| `is_dynamic_creative` | `false` (default) | Leave `false` in most cases. For multiple headlines/texts, prefer `creative_asset_groups_spec` (Flexible Ads) at the ad level instead — it does NOT need this flag. Only set to `true` if specifically using `asset_feed_spec` (legacy DCO) or placement-specific `asset_customization_rules`. |
| `targeting.age_min` | `18` | Default performant range |
| `targeting.age_max` | `55` | Default performant range |
| `targeting.genders` | Do NOT set | All genders |
| `targeting.publisher_platforms` | Do NOT set | Advantage+ Placements (automatic) |

**Workflow:** Fetch account details (Step 1) → get campaign details (Step 2) → list pixels (Step 3) → detect patterns (Step 4) → build targeting with interest search (Step 5) → call `facebook_propose_create_adset` directly with all auto-configured values. Do NOT call `user_input`. Do NOT show a summary before proposing — the user reviews and edits everything in the approval UI.

**EMPTY ACCOUNT (no existing adsets to detect patterns from):** If `account_structure.adsets` is empty, this is a NEW account. Do NOT stop and ask the user what to do. Proceed with creation using these defaults:
- `target_countries`: Use the account's timezone/locale to infer country (e.g., INR currency → `["IN"]`, USD → `["US"]`). If unsure, ASK the user.
- `daily_budget` (ABO only): **ASK the user** — you have no data to infer from. Use `user_input` with a single `daily_budget` number field.
- `adset_name`: Generate from campaign name + "Broad" (e.g., "GoMarble | Broad | Apr 2026")
- `targeting`: Broad targeting — geo_locations only, age 18-55, no interests/behaviors
- Everything else: use standard auto-configured values (IMPRESSIONS, OFFSITE_CONVERSIONS, ACTIVE, etc.)

---

## Complete Workflow (follow in exact order)

### Phase 1: Gather Information

**Step 1: Get Account Details** (if not already fetched)
Call `facebook_get_details_of_ad_account` with `act_id`.
Extract:
| Field | Where to Find | Use For |
|-------|--------------|---------|
| `currency` | Response root | `currency_code` param |
| `account_structure.adsets` | Response root | Detect targeting patterns, conversion events, budget ranges |

**Step 2: Get Parent Campaign Details** (MANDATORY)
Call `facebook_get_campaign_details` with `campaign_id` and `act_id`.
Extract:
| Field | Where to Find | Use For |
|-------|--------------|---------|
| `daily_budget` or `lifetime_budget` | Campaign response | `is_campaign_cbo` = true if either exists |
| `bid_strategy` | Campaign response | `campaign_bid_strategy` — determines if bid_amount is needed |
| `special_ad_categories` | Campaign response | Pass as `campaign_special_ad_categories` |
| `special_ad_category_country` | Campaign response | Pass as `campaign_special_ad_category_country` |
| `objective` | Campaign response | Must be OUTCOME_SALES for V1 |
| `status` | Campaign response | Verify not DELETED/ARCHIVED |

**STOP** if `facebook_get_campaign_details` fails — tell user campaign does not exist.

**Step 3: Get Pixel**
Call `facebook_list_pixels` with `act_id`.
- **1 pixel** → show to user for confirmation (e.g., "Found pixel: {name} ({id}). Using this for conversion tracking.")
- **Multiple pixels** → check which pixel is most used across existing ad sets' `promoted_object.pixel_id`. Show the most-used one as the recommended choice, list others. Ask user to confirm.
- **No pixels** → warn user that conversion tracking won't work

**Step 4: Detect Patterns from Existing Ad Sets**
From `account_structure.adsets`, extract:
| Pattern | Where to Find | Use For |
|---------|--------------|---------|
| Common countries | `adsets[].targeting.geo_locations.countries` | `target_countries` defaultValue |
| Age range | `adsets[].targeting.age_min`, `age_max` | Suggest age |
| Conversion event | `adsets[].promoted_object.custom_event_type` | Default event (usually PURCHASE) |
| Budget range | `adsets[].daily_budget` | `daily_budget` — use median. **If none found → ASK user, do NOT guess.** |
| Naming convention | `adsets[].name` | `adset_name` defaultValue |
| Bid amounts | `adsets[].bid_amount` | `bid_amount` — use median. **If none found → ASK user, do NOT guess.** |

**Step 5: Build Targeting with Interest/Behavior Search** (when user wants audience targeting)

Use `facebook_search_targeting` to find targeting option IDs for interests, behaviors, demographics, and other audience categories. **This tool operates at the ad set level — targeting is always configured on the ad set, never on the ad.**

#### When to use targeting search:
- User mentions specific interests (e.g., "people who like yoga", "anime fans", "runners")
- User wants to target specific behaviors (e.g., "engaged shoppers", "frequent travelers")
- User wants demographic targeting (e.g., "homeowners", "parents with toddlers")
- Creative analysis suggests a clear audience (e.g., fitness creative → search fitness interests)
- User explicitly asks for interest-based or behavior-based targeting

#### When to skip targeting search (use broad targeting):
- User says "broad targeting" or "let Meta optimize"
- No clear audience signals from creative or user
- Account patterns show broad targeting performs best

#### Search types:

| Search Type | When to Use | Required Params |
|-------------|-------------|-----------------|
| `adinterest` | Free-text search for interests | `query` (e.g., "yoga", "anime", "organic food", "running shoes") |
| `adinterestsuggestion` | Expand targeting with related interests | `interest_list` (array of interest IDs from prior search) |
| `adTargetingCategory` | Browse a full category | `class` (see categories below) |
| `adinterestvalid` | Validate interest IDs are still active | `interest_list` (array of interest IDs) |

#### Available category classes for `adTargetingCategory`:

| Class | Description | Example Use |
|-------|-------------|-------------|
| `interests` | Hobbies, entertainment, activities | "anime", "yoga", "gaming" |
| `behaviors` | Purchase behavior, device usage, travel | "engaged shoppers", "frequent travelers" |
| `demographics` | Education, relationship, work | "college graduates", "small business owners" |
| `life_events` | Recent milestones | "recently moved", "newly engaged" |
| `industries` | Professional industries | "technology", "healthcare" |
| `income` | Household income brackets | Top 10%, 25%, etc. |
| `family_statuses` | Parental status, family composition | "parents with toddlers", "new parents" |
| `home_ownership` | Homeowner vs renter | "homeowners", "renters" |
| `home_type` | Housing type | "apartment", "house" |
| `home_value` | Property value ranges | High-value homeowners |
| `household_composition` | Household makeup | "roommates", "living alone" |
| `net_worth` | Financial net worth brackets | High net worth individuals |
| `generation` | Generational cohorts | "millennials", "gen X" |
| `ethnic_affinity` | Cultural affinity | Multicultural targeting |
| `politics` | Political leanings | Political interest targeting |
| `markets` | Market segments | DMA/market-based targeting |
| `moms` | Parenting stage | "new moms", "moms of teenagers" |
| `office_type` | Work environment | "home office", "corporate" |
| `user_device` | Device targeting | "iPhone", "Samsung Galaxy" |
| `user_os` | Operating system targeting | "iOS", "Android" |

#### How to use search results in targeting:

The search returns objects with `id` and `name`. **Always include both `id` and `name`** when building targeting. Place results in the correct sub-key of `flexible_spec`:

```json
{
  "targeting": {
    "geo_locations": { "countries": ["US"] },
    "age_min": 25,
    "age_max": 55,
    "flexible_spec": [
      {
        "interests": [
          { "id": "6003139266461", "name": "Yoga" },
          { "id": "6003384248805", "name": "Meditation" }
        ],
        "behaviors": [
          { "id": "6002714895372", "name": "Engaged shoppers" }
        ]
      }
    ]
  }
}
```

#### flexible_spec sub-keys (must match the category of the targeting option):

| Sub-key | For Options From |
|---------|-----------------|
| `interests` | `adinterest` search or `adTargetingCategory` class=interests |
| `behaviors` | `adTargetingCategory` class=behaviors |
| `demographics` | `adTargetingCategory` class=demographics |
| `life_events` | `adTargetingCategory` class=life_events |
| `family_statuses` | `adTargetingCategory` class=family_statuses |
| `education_statuses` | Education-related demographics |
| `work_employers` | Employer targeting |
| `work_positions` | Job title targeting |
| `income` | `adTargetingCategory` class=income |
| `industries` | `adTargetingCategory` class=industries |
| `user_device` | `adTargetingCategory` class=user_device |
| `user_os` | `adTargetingCategory` class=user_os |

#### Targeting search workflow example:

1. User says "target people interested in anime and gaming"
2. Call `facebook_search_targeting({ act_id, search_type: "adinterest", query: "anime" })` — get results
3. Call `facebook_search_targeting({ act_id, search_type: "adinterest", query: "gaming" })` — get results
4. Pick the most relevant results (highest audience size, most specific match)
5. Optionally call with `search_type: "adinterestsuggestion"` + picked IDs to find related interests
6. Build `targeting.flexible_spec[].interests` with the selected `{ id, name }` pairs
7. Present to user in the proposal — they can edit/remove in the approval UI

#### Multiple flexible_spec groups (OR vs AND logic):

- Items **within** the same `flexible_spec` object are **OR** (match any)
- Items in **separate** `flexible_spec` objects are **AND** (must match all)

```json
{
  "flexible_spec": [
    { "interests": [{ "id": "123", "name": "Yoga" }, { "id": "456", "name": "Fitness" }] },
    { "behaviors": [{ "id": "789", "name": "Engaged shoppers" }] }
  ]
}
```
This means: (interested in Yoga OR Fitness) AND (Engaged shoppers)

**Step 6: Get Custom Audiences** (only if user mentions audiences)
Call `facebook_list_custom_audiences` with `act_id`.

### Phase 2: Auto-Configure (silently — do NOT show or ask user)

| Field | Value | Source |
|-------|-------|--------|
| `billing_event` | `IMPRESSIONS` | Always for Sales |
| `destination_type` | `WEBSITE` | Default for Sales |
| `optimization_goal` | `OFFSITE_CONVERSIONS` | Default for Sales — optimize for Purchase |
| `status` | `ACTIVE` | Default — goes live when an active ad is attached |
| `promoted_object` | `{ pixel_id: from Step 3, custom_event_type: "PURCHASE" }` | Pixel shown to user for confirmation in Step 3 |
| `is_campaign_cbo` | From Step 2 | true if campaign has budget |
| `campaign_bid_strategy` | From Step 2 | Pass the campaign's bid_strategy |
| `campaign_special_ad_categories` | From Step 2 | Pass the campaign's special_ad_categories |
| `campaign_special_ad_category_country` | From Step 2 | Pass the campaign's special_ad_category_country |
| `attribution_spec` | `[{ event_type: "CLICK_THROUGH", window_days: 7 }, { event_type: "VIEW_THROUGH", window_days: 1 }]` | Default 7d click + 1d view for conversions |
| `bid_strategy` | Do NOT set | Unless optimization_goal is IMPRESSIONS/REACH → then MUST set LOWEST_COST_WITHOUT_CAP |
| `is_dynamic_creative` | `false` (default) | Leave `false` — prefer `creative_asset_groups_spec` for text variations |
| `targeting` | From Step 5 | Interest/behavior/demographic search results in `flexible_spec`, geo from Step 4, age/gender defaults |

### Phase 3: Auto-Fix (apply silently, do NOT ask)

| Missing Field | Auto-Fix |
|--------------|----------|
| No audience / targeting | **Broad targeting** — geo_locations only, no interests/behaviors |
| No age range | **18-55** (default performant range) |
| No gender | All genders (omit field) |
| No placements | **Advantage+ Placements** (automatic — do NOT set publisher_platforms) |
| No attribution | **7d click + 1d view** (standard for conversions) |
| No conversion event | **PURCHASE** (for ecommerce/Sales campaigns) |

### Phase 4: Propose Directly

Call `facebook_propose_create_adset` immediately with all auto-configured values. Do NOT show a summary or ask for confirmation — the user reviews and edits everything in the approval UI.

---

## Guardrails

### CBO/ABO Budget Conflict (server enforces at execution)
| Condition | Action |
|-----------|--------|
| Parent campaign is CBO (has campaign-level budget) + ad set has daily_budget or lifetime_budget | **BLOCK** — "Parent campaign uses CBO. Remove budget from ad set." |
| Parent campaign is ABO (no campaign-level budget) + ad set has NO budget | **BLOCK** — "Parent campaign uses ABO. Ad set must have daily_budget or lifetime_budget." |

### Optimization Event Protection
| Condition | Action |
|-----------|--------|
| optimization_goal is NOT OFFSITE_CONVERSIONS and NOT VALUE | **WARN** — "You're optimizing for {goal} instead of conversions. For Sales campaigns, OFFSITE_CONVERSIONS or VALUE typically performs best." |
| optimization_goal is VALUE | **WARN** — "VALUE optimization requires a pixel with sufficient purchase events with varied values. If Meta rejects it, retry with OFFSITE_CONVERSIONS." |
| custom_event_type is NOT PURCHASE for ecommerce account | **WARN** — "You're optimizing for {event} instead of PURCHASE. For ecommerce, PURCHASE usually gives the best ROAS." |

### Budget Guardrails
| Condition | Action |
|-----------|--------|
| ABO budget < $1 USD equivalent | **BLOCK** — "Minimum budget is {minInLocal} {currency}" |
| ABO budget $1-$5 USD | **WARN** — "Budget is very low. Meta may struggle to exit learning phase." |
| ABO budget $5-$10 USD | **WARN** — "Budget is below recommended minimum for stable optimization." |

### Budget Fragmentation Guardrail
If user wants ABO + multiple ad sets under same campaign:
- Total budget across all ad sets < $20 USD → **WARN** — "Splitting {total} across {n} ad sets gives each only {per_adset}. Consider fewer ad sets or higher budget."

### Dynamic Creative Guardrail
| Condition | Action |
|-----------|--------|
| Ads will use `asset_feed_spec` but `is_dynamic_creative` not set to `true` | **BLOCK** — Meta returns "Dynamic creative ad sets allow for one active ad at most". Set `is_dynamic_creative: true` on the ad set. |

### Targeting Guardrails
| Condition | Action |
|-----------|--------|
| `flexible_spec` items missing `id` or `name` | **BLOCK** — both fields are required. Re-run `facebook_search_targeting` to get valid IDs. |
| `flexible_spec` has items in wrong sub-key (e.g., behavior in `interests`) | **WARN** — place each item in the sub-key matching its category (interests, behaviors, demographics, etc.) |
| If setting `user_device`, must also set `user_os` | **BLOCK** — Meta rejects device targeting without OS |
| `targeting.geo_locations` missing or empty | **BLOCK** — at least one location is required |
| `age_min` < 18 or `age_max` > 65 or `age_min` > `age_max` | **BLOCK** — invalid age range |
| Advantage+ audience (`targeting_automation.advantage_audience=1`) with `age_max` < 65 | **BLOCK** — Meta rejects hard age_max limits below 65 for Advantage+ audience. Either set age_max to 65, omit age_max, or disable Advantage+ audience. |

### Attribution Guardrail
| Condition | Action |
|-----------|--------|
| CLICK_THROUGH window_days = 1 for OFFSITE_CONVERSIONS/VALUE | **WARN** — "1-day click attribution gives Meta less conversion data. 7-day click is recommended for conversion campaigns." |

### Placement Guardrail
| Condition | Action |
|-----------|--------|
| Manual placements set (publisher_platforms specified) | **WARN** — "Manual placements restrict where Meta can show ads. Advantage+ Placements usually delivers better results at lower cost." |

### Spending Limits Rules
- Must be zero or positive numbers
- `daily_min_spend_target` must be <= `daily_spend_cap` (if both set)
- `lifetime_min_spend_target` must be <= `lifetime_spend_cap` (if both set)
- Do NOT mix daily and lifetime spending limits — use one type only

### Attribution Spec Rules (Meta enforces)

| Optimization Goal | Attribution Spec |
|-------------------|-----------------|
| OFFSITE_CONVERSIONS / VALUE | `[{ event_type: "CLICK_THROUGH", window_days: 7 }, { event_type: "VIEW_THROUGH", window_days: 1 }]` |
| IMPRESSIONS / REACH | `[{ event_type: "CLICK_THROUGH", window_days: 1 }, { event_type: "VIEW_THROUGH", window_days: 0 }]` — Meta rejects anything else |
| LINK_CLICKS / LANDING_PAGE_VIEWS | `[{ event_type: "CLICK_THROUGH", window_days: 1 }, { event_type: "VIEW_THROUGH", window_days: 0 }]` |

**ENGAGED_VIDEO_VIEW** (optional, video ads only): Add `{ event_type: "ENGAGED_VIDEO_VIEW", window_days: 1 }` to attribution_spec for video creatives. Valid window_days: 0 (none) or 1.
**CLICK_THROUGH** window_days: 1 or 7. **VIEW_THROUGH**: 0 or 1.

### Bid Amount Rules

| Campaign Bid Strategy | What to Do |
|----------------------|------------|
| Not set / LOWEST_COST_WITHOUT_CAP | Do NOT set bid_amount |
| COST_CAP | MUST set bid_amount — ask user for target cost per result |
| LOWEST_COST_WITH_BID_CAP | MUST set bid_amount — ask user for max bid |
| LOWEST_COST_WITH_MIN_ROAS | MUST set bid_constraints with roas_average_floor — ask user for target ROAS |

---

## Output After Creation

Show the user:
Give simple crisp summary of created adsets.

## Error Handling

Transient Meta API errors (code 2 "Please retry your request later", network errors) are automatically retried up to 2 times with backoff. No action needed from the LLM.

| Error | Action |
|-------|--------|
| "You can only set an ad set budget or a campaign budget" | Parent campaign is CBO. Remove `daily_budget` and `lifetime_budget` from ad set. |
| "pixel isn't eligible for value optimisation" | Pixel doesn't have enough varied purchase values. Retry with `optimization_goal=OFFSITE_CONVERSIONS` and `custom_event_type=PURCHASE` instead. |
| "Dynamic creative ad sets allow for one active ad at most" | Ad set needs `is_dynamic_creative: true` to use `asset_feed_spec` creatives. Re-create ad set with the flag set. |
| "Only dynamic creative ads can be created as the ad set is a dynamic creative ad set" | The ad set has `is_dynamic_creative: true` but the ad used flat fields. Use `asset_feed_spec` format for DCO ad sets. |

## Call the Tool

Pass `adset_configs` as a 1-element array. Never call the tool multiple times — batch all ad sets in one call.

When to use

Prepare Meta ad-set targeting, attribution and bids under a verified parent campaign. Use Meta Campaign Planning for campaign-level settings.

What you get

The complete original GoMarble guidance, with source attribution and declared limits.

How it works

Clarify scope, use available evidence, and apply the relevant source workflow within actual user authorization.

Requirements

Parent campaign, budget mode, pixel/event, targeting scope and authorized account context.

Delivery and review notes

Do not infer consent or sensitive/special-category eligibility from creative alone. Preserve full targeting and actual campaign budget mode. GoMarble connectors, referenced sibling skills and runtime dependencies are not bundled or installed by M11. Brief obvious-danger screening only; no functional test or comprehensive safety certification. Loading this text authorizes no external calls, account mutations or ad spend.

Starting prompt

Use Meta Ad Set Planning for [TASK]. Clarify Parent campaign, budget mode, pixel/event, targeting scope and authorized account context. Separate observed evidence from heuristics and recommendations. Check actual connector availability and approval semantics before any external action.

Not for

Claiming installed GoMarble tools, proven campaign outcomes or authorization to launch ads merely from loading this source.

What M11 added

German routing and explicit scope. Original attribution: GoMarble. Do not infer consent or sensitive/special-category eligibility from creative alone. Preserve full targeting and actual campaign budget mode. GoMarble connectors, referenced sibling skills and runtime dependencies are not bundled or installed by M11. Brief obvious-danger screening only; no functional test or comprehensive safety certification. Loading this text authorizes no external calls, account mutations or ad spend.

Original authorship remains with gomarble-ai/marketing-agent · Original source ↗

Original license & copyright

MIT License

Copyright (c) 2026 GoMarble

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

Source SHA-256: d5f5aefca79766c896d002fcd51c88bad4500e1fe13f5a20d73fb9d7245c1b93
Snapshot checked: 2026-09-28T16:19:52.867Z

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