SKILLEMALL.ai

AB background-delivery-sop

Standardize how agents handle tasks that run in the background, via sub-agents, or via ACP sessions, so completed work is always proactively delivered back to the user. Use when creating or improving agent workflows for async/background execution, fixing cases where results finish but are not sent, or teaching another agent how to do receipt → execution → final delivery without making the user chase for updates.

ClawHub Agent Skills author: wangwang0301 v1.2.0 MIT-0 2 files body ≈ 1 483 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ReferenceAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
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: 2. 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
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 14 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 70Failures and branches. 6 branches
    • 85Steps. 77 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1483 tokens
    • low 12 top-level sections: this looks like several domains in one skill

    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
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 415: enough signal without eating the budget
    • +4Structure: 25 headings
    • +3Step-by-step instructions: 77 items

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This is a text-only workflow guide for proactively reporting background task results, with no executable code or credential access.
    LLM: benign (high) · VirusTotal: · 29 May 2026