SKILLEMALL.ai

AC caching-strategies

Design multi-tier caching architectures for web applications — cache-aside vs write-through vs write-behind, TTL design, cache invalidation, Redis patterns, CDN configuration, browser caching, and stampede prevention. Use when choosing a caching pattern, designing cache invalidation strategies, implementing Redis caching, configuring Cache-Control headers, or preventing cache stampedes. Activate on "cache invalidation", "cache-aside", "write-through", "TTL", "Redis cache", "CDN caching", "cache stampede", "stale data", "browser cache". NOT for database query caching within an ORM, memoization of pure functions, or CPU-level caching.

curiositech/some_claude_skills Claude Code author: curiositech 4 files body ≈ 2 850 tokens Open the sourcegithub.com↗ analyzed 39 min ago

Design multi-tier caching architectures for web applications — cache-aside vs write-through vs write-behind, TTL design, cache invalidation, Redis patterns…

As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

GeneratorSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 54/100

    • 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. 10 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 13 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2850 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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 640: enough signal without eating the budget
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (10 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.