SKILLEMALL.ai

AB outclaw-setup

OutClaw setup: plugin inventory, connect outreach channels (Leadbay/LeadClaw, Gmail, Calendar, Slack, LinkedIn, WhatsApp, Calendly), capture the user's profile and org/product into the KB, and learn per-channel writing style. Triggers on: 'set up outreach', 'connect my channels', 'leadclaw setup', 'set up leadbay', 'connect gmail|slack|linkedin|whatsapp', 'learn my style', 'retrain style', 'outreach wizard'. Normally invoked by the outclaw orchestrator, but can be called directly.

ClawHub Agent Skills author: milstan v1.0.6 MIT-0 5 files body ≈ 2 556 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process B 70/100 · Nearly there — weak spots: result and completion, inputs and preconditions

GeneratorSlackWhatsAppGmailSales and CRMtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
B
70/100
Nearly there
Inputs and preconditions w 11
0
Result and completion w 14
40
Tools and files w 18
60
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 · 0

✓ No critical or high findings

Files scanned: 5. 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")

Process rating: all ten parameters 70/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 40Result and completion. Does not say what the result is
  • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 15 steps
  • 100Failures and branches. 6 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2556 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (9 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 485: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (2 of 3)

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

External checks

ClawHub: clean
This setup skill is purpose-aligned for configuring an outreach assistant, but it handles sensitive account connections and persistent profile data.
LLM: benign (medium) · VirusTotal: · 29 May 2026