AC tech-weekly-briefing
Generate weekly tech news briefings from 6 major English tech media sources (TechCrunch, The Verge, Wired, Ars Technica, MIT Technology Review, The Information). Aggregates news from the past 7 days, identifies hot stories covered by multiple outlets (2 or more media sources), and creates a curated report in the user's preferred language. Features automated daily RSS fetching, intelligent deduplication, low-quality content filtering, and interactive company-based navigation. Use when users request tech weekly briefing, 科技周报, 外媒科技新闻, weekly tech report, or want to monitor English tech media coverage with multi-source verification.
As a process C 55/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 1
✓ No critical or high findings
Medium and low: 1
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low Dangerous commands
cmd-cron-mentionSKILL.md:58Mentions editing / listing crontabcrontab -e
Files scanned: 8. 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 55/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 100Steps. 41 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2179 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 12 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
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 637: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 41 items
- +4Has examples (18 code blocks)
- +3All 3 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 85.