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AC plydb

Skill for using the PlyDB CLI to perform SQL analysis of connected data sources. Use for SQL queries across heterogeneous databases and files such as Postgres, MySQL, CSV, Parquet, JSON, Excel, SQLite, DuckDB, Google Sheets. Triggers on "plydb", "sql", "query", "data analysis", "parquet", "csv", "excel", "database".

ClawHub Agent Skills author: ypt v1.0.0 MIT-0 4 files body ≈ 821 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process C 55/100 · Has gaps — weak spots: steps, result and completion, inputs and preconditions

IntegrationGoogle SheetsPostgreSQLMySQLData and analyticstype 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
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
90
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Secrets in code secret-high-entropy-token references/config_schema.md:193
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "spreadsheet_id": "1Bxi…pms",
      quoted
    • low Secrets in code secret-high-entropy-token references/config_schema.md:204
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "spreadsheet_id": "1AbC…efg"
      quoted

    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 55/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 25Steps. 1 steps
    • 30Running it twice. 1 mutating operations with no state check
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 821 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3No numbered steps or checklist
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 3 example trigger phrases
    • +3Description length 317: enough signal without eating the budget
    • +4Structure: 9 headings
    • +4Has examples (6 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: suspicious
    This skill is coherent SQL-analysis guidance, but it can give an agent broad access to configured databases, files, cloud storage, and cached Google Sheets authorization with loose activation boundaries.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026