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AB prospecting

B2B manufacturing proactive prospecting. Search Google Maps for potential customers based on existing client profiles, enrich leads with business details, score and rank them, and output actionable CSV + JSON lead lists with custom sales openers. Includes chain store strategy: local call → identify procurement decision chain → escalate to corporate. Use when: finding new customers, prospecting, lead generation, searching for potential clients, building a call list, or when user mentions existing customers they want to find more like.

ClawHub Agent Skills author: sunrise_lfx v1.0.3 MIT-0 14 files body ≈ 5 703 tokens Open the sourceclawhub.ai↗ analyzed 27 h ago

B2B manufacturing proactive prospecting.

As a process B 65/100 · Nearly there — weak spots: result and completion, running it twice

ProcedureSales and CRMtype 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
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
B
65/100
Nearly there
Result and completion w 14
0
Running it twice w 4
30
When it triggers w 12
50
the three weakest of ten parameters · all ten

How to improve

  1. The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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: 14. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 5703 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "last_updated"
  • note frontmatter-key unknown frontmatter key "changelog"
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 65/100

  • 0Result and completion. Does not say what the result is
  • 30Running it twice. 4 mutating operations with no state check
  • 50When it triggers. No condition that starts the skill
  • 55Failures and branches. 1 branches
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 70Execution cost. Instruction body is 5703 tokens
  • 85Steps. 56 steps, 3 vague phrases
  • 100Tools and files. No external tools needed
  • 100Consistency. Name and required fields are in place
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

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
  • -220 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 539: enough signal without eating the budget
  • +4Structure: 24 headings
  • +3Step-by-step instructions: 56 items
  • +4Has examples (13 code blocks)
  • +4Reference files are cited in the instructions (3 of 7)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
This is a legitimate B2B prospecting skill, but it needs Review because it automatically broadens lead collection and writes prospecting learnings to cross-session memory without clear opt-in or limits.
LLM: suspicious (high) · 19 Aug 2026