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AB junta-leiloeiros

Coleta e consulta dados de leiloeiros oficiais de todas as 27 Juntas Comerciais do Brasil. Scraper multi-UF, banco SQLite, API FastAPI e exportacao CSV/JSON.

sickn33/agentic-awesome-skills Agent Skills author: sickn33 MIT 34 files body ≈ 1 492 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Coleta e consulta dados de leiloeiros oficiais de todas as 27 Juntas Comerciais do Brasil.

As a process B 78/100 · Nearly there — weak spots: result and completion, failures and branches

IntegrationData and analyticstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
B
78/100
Nearly there
Failures and branches w 10
0
Result and completion w 14
40
Inputs and preconditions w 11
70
the three weakest of ten parameters · all ten

The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills

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: 34. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "risk"
    • note frontmatter-key unknown frontmatter key "source"
    • note frontmatter-key unknown frontmatter key "date_added"
    • note frontmatter-key unknown frontmatter key "tools"

    Process rating: all ten parameters 78/100

    • 0Failures and branches. Linear process with no failure handling
    • 40Result and completion. Does not say what the result is
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 27 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1492 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress
    • low 19 top-level sections: this looks like several domains in one skill

    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)
    • +3Output format is not stated: the model decides each time
    • -4Absolute local paths (C:\Users, /home/…): not portable
    • -2localhost URLs: will not work for another user
    • -31 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 157: enough signal without eating the budget
    • +4Structure: 20 headings
    • +3Step-by-step instructions: 27 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.