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AC phoenixclaw-ledger

Passive financial tracking plugin for PhoenixClaw. Automatically detects expenses and income from conversations and payment screenshots. Use when: - User mentions money/spending (any language) - User shares payment screenshots (WeChat Pay, Alipay, etc.) - User asks about finances ("How much did I spend?", "My budget") - User wants expense reports ("Monthly summary", "Spending analysis")

modbender/skill-library-mcp Agent Skills author: modbender MIT 18 files body ≈ 1 307 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Passive financial tracking plugin for PhoenixClaw.

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

ProcedureData and analyticsWriting and documentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
93
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
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: 18. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "depends"
    • note frontmatter-key unknown frontmatter key "protocol_version"
    • note frontmatter-key unknown frontmatter key "min_core_version"
    • note frontmatter-key unknown frontmatter key "hook_point"
    • note frontmatter-key unknown frontmatter key "data_access"
    • note frontmatter-key unknown frontmatter key "export_to_journal"

    Process rating: all ten parameters 62/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 34 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1307 tokens
    • 100Running it twice. No mutating operations

    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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +3Description length 390: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 34 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (9 of 9)

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