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AB golang-samber-oops

Structured error handling in Golang with samber/oops — error builders, stack traces, error codes, error context, error wrapping, error attributes, user-facing vs developer messages, panic recovery, and logger integration. Apply when using or adopting samber/oops, or when the codebase already imports github.com/samber/oops.

ClawHub Agent Skills author: Samuel Berthe v1.2.0 MIT-0 4 files body ≈ 2 366 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 72/100 · Nearly there — weak spots: inputs and preconditions, running it twice

IntegrationGitHubSoftware developmenttype 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
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
72/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
Failures and branches w 10
50
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 3. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "paths"

    Process rating: all ten parameters 72/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 14 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2366 tokens
    • 100Progress reporting. Reports progress
    • low No test case covers injection arriving through data

    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)
    • +2Single-language instructions
    • +3Description length 324: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 14 items
    • +3Output format is stated explicitly
    • +4Has examples (11 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This Go error-handling skill is coherent, but its examples can lead agents to put personal data, HTTP request details, and raw input payloads into errors that are commonly logged or exported.
    LLM: suspicious (medium) · VirusTotal: · 22 Aug 2026