BD instagram-marketing
Generate Instagram marketing content from product URLs. Extract product information and create engaging Instagram posts with image suggestions, captions, and hashtags optimized for engagement. Use when user provides a product URL from e-commerce sites like Amazon, Shopify, Taobao, etc. and wants Instagram marketing content such as Image/text post ideas, engaging captions with CTAs, hashtag strategy, or Story/reels content suggestions.
Generate Instagram marketing content from product URLs.
As a process D 46/100 · Unfinished process — References files that are not bundled: references/CAMPAIGN_STRATEGY.md, references/FASHION.md, references/TECH.md
The same skill appears in 4 more places: ClawHub, ClawHub, ClawHub, ClawHub
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/CAMPAIGN_STRATEGY.md - warning
missing-refreference to a missing file: references/FASHION.md - warning
missing-refreference to a missing file: references/TECH.md - warning
missing-refreference to a missing file: references/ENGAGEMENT_TACTICS.md - warning
missing-refreference to a missing file: templates/CAROUSEL_TEMPLATE.md - warning
missing-refreference to a missing file: templates/STORY_TEMPLATE.md - warning
missing-refreference to a missing file: templates/REEL_TEMPLATE.md
Process rating: all ten parameters 46/100
- 0Tools and files. 7 referenced file(s) missing: references/CAMPAIGN_STRATEGY.md, references/FASHION.md, references/TECH.md
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 50Failures and branches. 0 branches, has a failure section
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 84 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1773 tokens
- low 10 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +3Description length 438: enough signal without eating the budget
- +4Structure: 36 headings
- +3Step-by-step instructions: 84 items
- +3Output format is stated explicitly
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.
In the sandbox Скрипты не запустились
The skill's scripts were run in a throwaway machine: no network, fake keys in the home directory, a tracer watching. We wrote down what they did. Reaching for the network or for secrets caps the technical grade at C; a quiet run adds no points.
Запущено 1 скрипт; каждому дали двадцать секунд, поддельный домашний каталог с ключами и сеть, в которой ничего нет.
Ни один не дошёл до работы — им не хватило зависимостей, аргументов или файлов. Это не отзыв о поведении: наблюдать было не за чем.
scripts/extract_product.py | не запустился: NameError: name 'BeautifulSoup' is not defined |
25 Oct 2026