SKILLEMALL.ai

AB multi-task

Orchestrate parallel execution of batch tasks by splitting work into independent units and dispatching them to multiple subagents simultaneously. Use this skill whenever the user has multiple similar independent tasks — such as processing a batch of files (PDFs, DOCX, images, CSVs), developing multiple pages or components, generating multiple reports, or any scenario involving 'each', 'every', 'all', 'batch', or a list of similar items. Also trigger when the user provides a numbered list of tasks, references a folder of files to process, or describes repetitive work across multiple inputs. Even if the user doesn't explicitly say 'parallel' or 'batch', if the work naturally decomposes into 3+ independent units of similar type, use this skill to maximize throughput.

ClawHub Agent Skills author: Bright Ween v1.0.0 3 files body ≈ 3 070 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 71/100 · Nearly there — weak spots: inputs and preconditions, running it twice

GeneratorWordData and analyticsInfrastructuretype 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
71/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Tools and files w 18
60
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 71/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 58 steps, 2 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 5 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3070 tokens
    • 100Progress reporting. Reports progress

    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
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 774: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 58 items
    • +3Output format is stated explicitly
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

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

    External checks

    ClawHub: clean
    This is an instruction-only skill for splitting batch work across parallel subagents, with no hidden code or evidence of credential theft, exfiltration, or persistence.
    LLM: benign (high) · VirusTotal: benign · 28 May 2026