SKILLEMALL.ai

AB biweekly-work-report

Record daily work items into structured logs and generate weekly biweekly reports from accumulated data. Trigger when the user says 记录工作 记录一下 今天做了 生成周报 本周周报 双周报 工作汇报 周报 or any variation of logging work or producing a work report.

ClawHub Agent Skills author: AppleASugar v1.0.0 MIT-0 6 files body ≈ 1 037 tokens Open the sourceclawhub.ai analyzed 2 d ago

Record daily work items into structured logs and generate weekly biweekly reports from accumulated data.

As a process B 70/100 · Nearly there — weak spots: inputs and preconditions, failures and branches

GeneratorData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Failures and branches w 10
0
Result and completion w 14
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: 6. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "agent_created"

    Process rating: all ten parameters 70/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 16 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1037 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +1No license
    • +2Single-language instructions
    • +3Description length 229: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 16 items
    • +3Output format is stated explicitly
    • +4Has examples (4 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill is a local Markdown work-log and report generator with disclosed file writes, but users should be aware it keeps persistent work-history files.
    LLM: benign (high) · VirusTotal: · 26 Jun 2026