BC short-form-market-research-brain
Short-form video market research via the Virlo API — viral niche research, trend tracking, creator vetting, hashtag, sound, and hook intelligence across TikTok, YouTube Shorts, and Instagram Reels. Use when the user wants to research what's working in a niche, find rising creators, monitor trends, get viral hooks (opening lines) to model, or analyze social video performance.
Short-form video market research via the Virlo API — viral niche research, trend tracking, creator vetting, hashtag, sound, and hook intelligence across…
As a process C 56/100 · Has gaps — weak spots: result and completion, inputs and preconditions, execution cost
How to improve
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
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low Exfiltration
net-credential-useSKILL.md:31Credential used in a network call (verify the destination is the intended service) (documentation of a security skill; the skill's own vendor host)curl -H "Authorization: Bearer $VIRLO_API_KEY" https://api.virlo.ai/v1/account/balance
security skillvendor-host
Files scanned: 11. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 17805 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage" - note
edit-residuethe text marks something as outdated (lines 173, 193, 195, 287, 288, 300): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 56/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 10Execution cost. Instruction body is 17805 tokens: crowds the task out of the window
- 30Running it twice. 50 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 224 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 377: enough signal without eating the budget
- +4Structure: 28 headings
- +3Step-by-step instructions: 224 items
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.