SKILLEMALL.ai

AB agent-essentials

Meta-skill for capability expansion and cautious self-improvement. USE WHEN (a) a request suggests a missing capability, external platform support, workflow automation, integration work, or any reusable process that may benefit from skill discovery before giving up — common phrases include "automate X", "integrate with X", "support X platform", "帮我自动化X", "对接X", "做一个工具来X"; OR (b) a meaningful failure, user correction, recurring mistake ("again", "this is the Nth time", "又错了", "这是第N次了"), or better workflow should be captured and routed into a durable file (AGENTS.md / TOOLS.md / USER.md / SOUL.md). DO NOT use for one-off questions or trivial noise.

ClawHub Agent Skills author: nathanshan v1.1.5 MIT-0 2 files body ≈ 1 195 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 66/100 · Nearly there — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Inputs and preconditions w 11
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 66/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 4 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. No external tools needed
    • 100Steps. 30 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1195 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (5 tags): a typed call is more reliable

    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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 7 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 654: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 30 items
    • +4Has examples (2 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 93.

    External checks

    ClawHub: clean
    This instruction-only skill is coherent with its purpose: it helps agents find missing capabilities and save small learning notes, with the main persistence behavior disclosed.
    LLM: benign (high) · VirusTotal: · 29 May 2026