SKILLEMALL.ai

AB github-triage

GitHub notification auto-triage via email channel. Classifies incoming GitHub notification emails into three tiers: (1) CI failures and security alerts → immediate forward with [紧急] tag, (2) PR reviews and merges → buffered for daily summary, (3) everything else → silent archive. Use when: an inbound email on the ghbot sub-mailbox is a GitHub notification. Requires: mail-cli, email channel plugin (@clawmail/email). NOT for: non-GitHub emails or manual email composition.

ClawHub Agent Skills author: DevincodeL v1.0.1 MIT-0 4 files · 1 script body ≈ 880 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

IntegrationGitHubInfrastructureWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
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: 4. 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
    • 30Running it twice. 11 mutating operations with no state check
    • 50When 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. 21 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 880 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 474: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 21 items
    • +4Has examples (7 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: suspicious
    The skill appears to forward GitHub notification content and persist related metadata, which is sensitive enough to require review before installation.
    LLM: suspicious (medium) · VirusTotal: · 29 May 2026