SKILLEMALL.ai

AB factoriago

FactoriaGo platform assistant — AI-driven academic paper revision and resubmission. Activate when user mentions: FactoriaGo, revise paper, reviewer comments, resubmit, LaTeX editing, paper revision, manuscript revision, journal resubmission, reviewer response, academic paper editing, revision letter, respond to reviewers, paper submission. Supports: (1) onboarding new users to factoriago.com, (2) calling FactoriaGo API to manage projects/tasks/files, (3) generating reviewer response letters, (4) analyzing reviewer feedback and creating revision strategies.

ClawHub Agent Skills author: Ge Yanhao v2.9.7 MIT-0 7 files body ≈ 1 396 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 67/100 · Nearly there — weak spots: result and completion, when it triggers, progress reporting

IntegrationLaTeXResearchWriting and documentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
When it triggers w 12
20
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: 7. 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 67/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 51 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1396 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 562: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 51 items
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    The skill appears aimed at academic revision support, but it repeatedly normalizes unsafe handling of account sessions and API keys that users should review before installing.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026