SKILLEMALL.ai

AB pocketbook

Record, query, complete, correct, and undo personal bookkeeping entries through short natural-language conversation, with local JSONL and Markdown persistence plus support for incomplete entries. Use when the user is directly operating a personal ledger: adding an expense, income, refund, or transfer; asking for spending or income summaries; reviewing recent entries; or modifying, completing, or undoing the latest or recent entries. Trigger on explicit requests such as "记账", "记一笔", "入账", "查账", "汇总", "统计", "补全上一笔", and "撤销上一笔", and on short transaction utterances with clear money movement such as "午饭28", "打车36", "工资到账12000", or "退款80". Do not use for generic note-taking, bookkeeping-software design, budgeting or investment discussion, tax or accounting advice, invoice or OCR tasks, reimbursement workflows, or product price lookup unless the user is explicitly operating the ledger.

ClawHub Agent Skills author: SuRu711 v1.0.0 MIT-0 11 files body ≈ 1 448 tokens Open the sourceclawhub.ai analyzed 3 d ago

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

ProcedureFinancetype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
94
Run on models
none yet
Process rating
B
65/100
Nearly there
Progress reporting w 2
0
Inputs and preconditions w 11
30
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: 11. 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

    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 9 mutating operations with no state check
    • 40Consistency. Frontmatter name (pocketbook) differs from the folder (pocket-book)
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Failures and branches. 6 branches
    • 85Steps. 50 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 1448 tokens
    • low The response is described with custom markup (17 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

    • +3Description length 892: 120–800 characters recommended
    • -31 of 6 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +4Description says when NOT to use the skill
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 50 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    Pocketbook is a local personal-ledger skill that clearly stores and edits bookkeeping files for the stated purpose, with no evidence of hidden network access or destructive behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026