SKILLEMALL.ai

BB analyze-performance

Statically scans the entire local Power Pages codebase for performance anti-patterns — unpaginated Power Pages lists, webpages/web templates used as custom data APIs, FetchXML over-fetching / N+1 / advanced query hints / cache bypassing, unbounded Web API queries, disabled header/footer output caching, sign-in and page tracking, main-thread-blocking JS, CSS @import, frequent Web API polling, and oversized assets — then enriches findings with AI-driven suggestions and mitigations grounded in the affected customer-code snippets, reports them, and offers safe auto-fixes with per-fix approval. Use when the user wants to: "check performance", "perf check", "find performance issues", "why is my site slow", "optimize my Power Pages site", "find anti-patterns", "review FetchXML performance", "is my site over-fetching data", or "audit site performance".

microsoft/power-platform-skills Claude Code author: microsoft 4 files · 2 scripts body ≈ 4 835 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Statically scans the entire local Power Pages codebase for performance anti-patterns — unpaginated Power Pages lists, webpages/web templates used as custom…

As a process B 77/100 · Nearly there — weak spots: result and completion

AnalyzerSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
95
Quality 40%
93
Run on models
none yet
Process rating
B
77/100
Nearly there
Result and completion w 14
0
When it triggers w 12
70
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Edit Bash Glob Grep AskUserQuestion TaskCreate TaskUpdate TaskList mcp__plugin_power-pages_microsoft-learn__microsoft_docs_search mcp__plugin_power-pages_microsoft-learn__mic

    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 77/100

    • 0Result and completion. Does not say what the result is
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Execution cost. Instruction body is 4835 tokens
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 44 steps
    • 100Failures and branches. 3 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 15 top-level sections: this looks like several domains in one skill
    • low The response is described with custom markup (10 tags): a typed call is more reliable

    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 856: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 9 example trigger phrases
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 44 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 2 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.