BB dataify-twitter-profile-by-profileurl
Collect an X/Twitter profile from a known profile URL. Do not use for posts, keyword search, or arbitrary X URLs.
Collect an X/Twitter profile from a known profile URL.
As a process B 69/100 · Nearly there — weak spots: result and completion
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- 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 · 5
✓ No critical or high findings
Medium and low: 5
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medium Dangerous commands
cmd-shell-rcSKILL.md:60Writes to a shell startup fileecho 'export DATAIFY_API_TOKEN="your_token_here"' >> ~/.bashrc
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medium Dangerous commands
cmd-shell-rcSKILL.md:66Writes to a shell startup fileecho 'export DATAIFY_API_TOKEN="your_token_here"' >> ~/.zshrc
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medium Dangerous commands
cmd-shell-rcSKILL.zh-CN.md:48Writes to a shell startup fileecho 'export DATAIFY_API_TOKEN="your_token_here"' >> ~/.bashrc
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medium Dangerous commands
cmd-shell-rcSKILL.zh-CN.md:55Writes to a shell startup fileecho 'export DATAIFY_API_TOKEN="your_token_here"' >> ~/.zshrc
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low Secrets in code
secret-password-literalscripts/task_runtime.py:38Hard-coded password / key literal (may be an example)api_key = api_key[7:].strip()
Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 69/100
- 0Result and completion. Does not say what the result is
- 50When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 100Steps. 47 steps
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2071 tokens
- 100Running it twice. No mutating operations
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
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
- +3Description length 113: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -36 of 8 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +4Structure: 10 headings
- +3Step-by-step instructions: 47 items
- +4Has examples (9 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.