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AB brek-ai-skill

Integrate with Brek Partner Core Chat API for hotel-search and booking assistant flows. Use when an agent needs to create or continue Brek chat sessions, send user events safely, enforce anti-abuse call controls, and run payment setup or payment confirmation without collecting raw card data.

ClawHub Agent Skills author: leo9 v1.0.2 6 files body ≈ 834 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 74/100 · Nearly there — weak spots: when it triggers, consistency, running it twice

IntegrationInfrastructureAI and agentstype 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
74/100
Nearly there
When it triggers w 12
20
Running it twice w 4
30
Consistency w 8
40
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: 6. 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 74/100

    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 1 mutating operations with no state check
    • 40Consistency. Frontmatter name (brek-ai-skill) differs from the folder (brek-ai)
    • 60Result and completion. Output format stated, no completion criterion
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Tools and files. No external tools needed
    • 100Steps. 40 steps
    • 100Failures and branches. 2 branches, has a failure section
    • 100Execution cost. Instruction body is 834 tokens
    • 100Progress reporting. Reports progress
    • low The response is described with custom markup (3 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 292: enough signal without eating the budget
    • +4Structure: 8 headings
    • +3Step-by-step instructions: 40 items
    • +3Output format is stated explicitly
    • +4Has examples (0 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

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

    External checks

    ClawHub: clean
    This skill is a coherent Brek hotel-booking API integration that discloses its network calls, API key use, booking/payment authority, and storage needs.
    LLM: benign (high) · VirusTotal: suspicious · 28 May 2026