SKILLEMALL.ai

AB comeback-buddy

帮用户分析对话场景并生成巧妙的回怼话术。Use when the user provides chat screenshots, conversation transcripts, or describes a situation where they felt spoken down to, bullied in conversation, or wished they had a better comeback. Inputs include chat context (text or screenshots). Outputs: 1) Situation analysis (who's right, power dynamics, emotional undercurrents), 2) Ready-to-use comeback lines (multiple options with different tones), 3) Generalizable techniques for similar future encounters. Triggers on phrases like "帮我回怼", "怎么怼回去", "帮我分析这段对话", "这句话怎么回", "被人说了不知道怎么回", "吵架没发挥好", "怼怼". Works across scenarios: couples, friends, colleagues, bosses, family, customer disputes. Covers mild comebacks through nuclear options (leave-the-job level).

ClawHub Agent Skills author: wxhzzsf v1.1.0 MIT-0 4 files body ≈ 549 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
96
Run on models
none yet
Process rating
B
65/100
Nearly there
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: 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 65/100

    • 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
    • 30Running it twice. 1 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 549 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)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 731: enough signal without eating the budget
    • +4Structure: 5 headings
    • +3Step-by-step instructions: 35 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 96.

    External checks

    ClawHub: clean
    This is an instruction-only comeback coaching skill with disclosed aggressive-response options but no hidden code, installs, credential use, or persistence.
    LLM: benign (high) · VirusTotal: · 29 May 2026