AC stock-earnings-analysis
Earnings analysis for US stocks, organized by fiscal quarter: what the company reported, the editorial headline, marquee KPI highlights with year-over-year deltas, guidance as management phrased it, and an earnings-call summary, plus SEC risk-factor diffs attached to their quarter, the AI takeaway signal, recent reporters, the forward calendar, the importance-ranked view of who just reported and who reports next, the market-wide beat rate baseline, and the measured price reaction to each past announcement. Every claim carries its fiscal period and report date, and absence is stated rather than skipped. Use for "analyze AAPL earnings", "earnings report analysis", "earnings call summary", "who reported earnings this week", "post earnings review", "upcoming earnings preview", "which earnings mattered this week", "earnings beat rate", "how does NVDA move on earnings". Read-only. No trading, no purchases, no write operations, no wallet access.
Earnings analysis for US stocks, organized by fiscal quarter: what the company reported, the editorial headline, marquee KPI highlights with year-over-year…
As a process C 58/100 · Has gaps — weak spots: when it triggers, 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 · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
body-longSKILL.md body ≈ 8484 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage" - note
frontmatter-keyunknown frontmatter key "requires" - note
frontmatter-keyunknown frontmatter key "primaryEnv"
Process rating: all ten parameters 58/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 8 mutating operations with no state check
- 40Execution cost. Instruction body is 8484 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 69 steps
- 100Failures and branches. 2 branches, has a failure section
- 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
- low 12 top-level sections: this looks like several domains in one skill
- low The skill ranks results itself: that belongs to the system behind the tool, not the model
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 952: 120–800 characters recommended
- +1No license
- +2Single-language instructions
- +5Description quotes 9 example trigger phrases
- +4Structure: 26 headings
- +3Step-by-step instructions: 69 items
- +3Output format is stated explicitly
- +4Has examples (0 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.