AB alon-fact-check
USE WHEN user wants to verify factual claims from text or a URL with authoritative sources, or trace a claim back to its original or official source URL. Extracts explicit verifiable claims, searches primary or professional fact-checking sources, and returns a structured credibility report or source trace with links. Do not use for opinion editing, general research summaries, or advice generation.
As a process B 72/100 · Nearly there — weak spots: running it twice, progress reporting
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 · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 5345 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "trigger"
Process rating: all ten parameters 72/100
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Failures and branches. 19 branches
- 70Execution cost. Instruction body is 5345 tokens
- 85Steps. 128 steps, 2 vague phrases
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 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
- -213 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 400: enough signal without eating the budget
- +4Structure: 15 headings
- +3Step-by-step instructions: 128 items
- +3Output format is stated explicitly
- +4Has examples (2 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.