SKILLEMALL.ai

AC frustration-translator

Detect user frustration in prompts and translate charged/emotional language into clear, actionable instructions. Use when user messages contain vague anger ("this is garbage"), compressed expectations ("just fix it"), repeated complaints about the same issue, ALL CAPS, or emotional language that obscures what they actually need done. Critical for finite context windows where misinterpreting a frustrated prompt wastes tokens on the wrong task. Improves over time by logging frustration patterns and their resolved meanings.

ClawHub Agent Skills author: KairoKid v1.0.0 MIT-0 3 files body ≈ 329 tokens Open the sourceclawhub.ai analyzed 5 d ago

As a process C 59/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerAI and agentsWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
59/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
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: 3. 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 59/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 4 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 329 tokens

    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)
    • -41 reference files, but SKILL.md never points to them: the model will not open them
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 2 example trigger phrases
    • +3Description length 526: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 4 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: suspicious
    This Markdown-only skill is not malware, but it asks agents to persist raw frustrated user messages and act on inferred intent too aggressively.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026