SKILLEMALL.ai

AB thesis-results-writer

Write detailed, academically rigorous Chinese results chapters or results sections for theses, dissertations, and undergraduate papers from a user's quantitative data, tables, statistical outputs, research questions, hypotheses, qualitative themes, interview excerpts, case summaries, or extra information. Use when users ask to write, expand, polish, organize, or structure only the Results/Chapter Four/研究结果/结果分析/资料分析结果 section, including descriptive statistics, hypothesis testing, research-question results, tables, figures, additional analyses, qualitative themes, case results, and chapter summary.

ClawHub Agent Skills author: John Do v1.0.0 MIT-0 4 files body ≈ 1 101 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process B 75/100 · Nearly there — weak spots: when it triggers, progress reporting

GeneratorData and analyticsResearchInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
75/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Failures and branches w 10
55
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 75/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1101 tokens
    • 100Running it twice. No mutating operations

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 604: enough signal without eating the budget
    • +4Structure: 7 headings
    • +3Step-by-step instructions: 34 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.

    External checks

    ClawHub: clean
    This is a low-risk writing aid for Chinese thesis results sections, with no code execution, credential use, persistence, or hidden data movement found.
    LLM: benign (high) · VirusTotal: · 29 May 2026