AC floods-market-sales
Market context, strategic thesis, case studies, proof points, sales pipeline, and B2B communication guidelines for Floods. Use this skill when working on pitch decks, proposals, sales emails, VSL scripts, pilot frameworks, competitive analysis, or any outbound communication targeting mobile gaming studios. Also use for understanding the mobile gaming UA landscape and why organic distribution matters. Always trigger on any mention of: Moon Active, Coin Master, pilot proposal, UA strategy, mobile gaming market, case studies, proof points, sales pipeline, B2B communications for Floods, or any request to write or refine a pitch, deck, proposal, or sales asset. When in doubt, load this skill — it contains the commercial reasoning that should anchor all Floods materials.
As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
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 · 0
✓ No critical or high findings
Files scanned: 2. 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
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (floods-market-sales) differs from the folder (marketsales)
- 100Tools and files. No external tools needed
- 100Steps. 29 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 1610 tokens
- 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 775: enough signal without eating the budget
- +4Structure: 13 headings
- +3Step-by-step instructions: 29 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.