SKILLEMALL.ai

AB discussion-conventions-diagnosis

Diagnose academic-writing conventions in the Discussion of an English psychology research paper. Checks the Achievement/Contribution statement (placement, type among 4 — method / results / impact / application), limitations writing, future-work conventions, citation density and function, and the use of "happy words" / appropriate hedging. Triggers on "check conventions", "contribution statement", "happy words", "limitation check", "future work check", "Discussion 学术规范", "讨论贡献", "讨论局限性", etc. Does NOT generate or rewrite prose.

ClawHub Agent Skills author: laninga v1.0.0 MIT-0 11 files body ≈ 1 034 tokens Open the sourceclawhub.ai analyzed 3 d ago

Diagnose academic-writing conventions in the Discussion of an English psychology research paper.

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

AnalyzerResearchInfrastructuretype 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: 11. 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. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1034 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 7 example trigger phrases
    • +3Description length 532: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 16 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 a read-only academic writing diagnostic skill with no executable behavior; the only notable issue is that some trigger phrases are broad enough to activate outside its niche.
    LLM: benign (high) · VirusTotal: · 24 Aug 2026