AC katelynn-lead-gen
Katelynn Lead Gen — Intelligent full-cycle lead generation, warm prospect qualification, and multi-channel outreach. Use this skill any time the user wants to find potential customers, qualify them as warm vs cold, build deep company profiles, and reach out via email or phone. Triggers include: "find me leads", "build a prospect list", "write cold emails", "find warm prospects", "research companies for outreach", "generate outreach for my ICP", "who should I contact about X", "draft personalized emails", "help me fill my pipeline", "find prospects and reach out", "run Katelynn", "use Katelynn", "build a contact list", or any combination of prospecting + qualification + outreach. Also triggers when the user describes an ICP or target market and wants to act on it. Includes warm lead routing to a phone transfer or sales team SMS.
Katelynn Lead Gen — Intelligent full-cycle lead generation, warm prospect qualification, and multi-channel outreach.
As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- 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: 7. 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 64/100
- 0Result and completion. Does not say what the result is
- 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
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 51 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2865 tokens
- 100Progress reporting. Reports progress
- low 10 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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 839: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 13 example trigger phrases
- +4Structure: 23 headings
- +3Step-by-step instructions: 51 items
- +4Has examples (3 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.