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BC airbnb-gateway

A skill for safe, coherent Airbnb operations in OpenClaw-style agent environments. It standardizes how agents check inbox threads, inspect reservations and booking state, review calendar context, draft guest replies, send messages safely, verify whether a send actually appeared in the live Airbnb thread, and make operator-approved, per-operation, independently-verified calendar mutations (block/open dates, nightly price). It teaches a strict operating model: prefer Airbnb-native endpoints before generic browser automation; treat send acknowledgments as attempted, not automatically confirmed; verify outbound messages in the live thread UI before declaring success; and never auto-resend from ambiguous or unconfirmed state. Designed to reduce duplicate messages, normalize agent behavior, and provide a safer foundation for Airbnb messaging, bookings, and calendar workflows — useful standalone today and as a companion to a more formal Airbnb adapter/tool layer tomorrow.

ClawHub Agent Skills author: Jason Vaughan v0.2.1 MIT-0 18 files body ≈ 3 436 tokens Open the sourceclawhub.ai↗ analyzed 33 h ago

A skill for safe, coherent Airbnb operations in OpenClaw-style agent environments.

As a process C 63/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

IntegrationPlaywrightAI and agentsOperations and projectstype 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
B
86/100
safety, quality, tests
Safety 60%
96
Quality 40%
71
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Progress reporting w 2
0
Inputs and preconditions w 11
30
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 4

✓ No critical or high findings

Medium and low: 4
  • low Exfiltration net-credential-use references/calendar-mutation-procedure.md:20
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    `Authorization: Bearer $CLAWBRIDGE_TOKEN`, base `http://host…201`.
    quoted
  • low Exfiltration net-credential-use references/calendar-mutation-procedure.md:31
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    `curl -s -H "Authorization: Bearer $CLAWBRIDGE_TOKEN" http://host…201/tools/browser/snapshot | grep -i -m5 "blocked\|Save\|Selected dates"`
    quoted
  • low Exfiltration net-credential-use references/calendar-mutation-procedure.md:50
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    `curl -s -H "Authorization: Bearer $CLAWBRIDGE_TOKEN" http://host…201/tools/browser/snapshot | grep -i blocked`
    quoted
  • low Exfiltration net-credential-use references/calendar-mutation-procedure.md:61
    Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)
    `curl -s -X POST -H "Authorization: Bearer $CLAWBRIDGE_TOKEN" -H "Content-Type: application/json" -d @/tmp/eval.json http://host…201/tools/browser/eval`
    quoted

Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")
  • note frontmatter-key unknown frontmatter key "risk"
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "maintainer"

Process rating: all ten parameters 63/100

  • 0Result and completion. Does not say what the result is
  • 0Progress reporting. Says nothing while it works
  • 30Inputs and preconditions. Does not say what the process needs to start
  • 30Running it twice. 45 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 51 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3436 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 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)
  • +3Description length 979: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 51 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This documentation-only Airbnb operations skill is high-impact but clearly scoped, approval-gated, and scanner-clean, with no evidence of hidden data theft or destructive behavior.
LLM: benign (high) · VirusTotal: · 10 Jul 2026