AF google-social-media-finder
Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and follower count across X, Instagram, Facebook, LinkedIn, TikTok, YouTube, Pinterest, Reddit, Snapchat, Threads, and more. Use when user wants to find someone's social media accounts, look up social profiles, discover where a person is active online, find brand social media pages, search social accounts by name, track digital footprint, find influencer profiles, check a company's social presence, locate a public figure's profiles, social media lookup, social media finder, find accounts across platforms, social profile search, online presence discovery, who is this person on social media, what social media does X use, find username across platforms.
Searches Google to discover social media profiles associated with a person, brand, or username; returns platform name, profile URL, username, bio snippet, and…
As a process F 49/100 · Will not run — References files that are not bundled: scripts/*.py
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: scripts/*.py
Process rating: all ten parameters 49/100
- 0Tools and files. 1 referenced file(s) missing: scripts/*.py
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (google-social-media-finder) differs from the folder (google-social-media-finder-skill)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 9 steps, 3 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1451 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)
- +3Description length 813: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 13 headings
- +3Step-by-step instructions: 9 items
- +4Has examples (4 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.