AC lead-enrichment
Turn a name into a full dossier in seconds. Feed in a name + company (or email, or LinkedIn URL) and get back a rich profile with social links, bio, company intel, recent activity, and personalized talking points. Aggregates data from multiple public sources — LinkedIn, Twitter, GitHub, company websites, news — so you can skip the manual research and jump straight to personalized outreach. Your agent does the detective work while you close deals. Supports single enrichment, batch processing, and multiple output formats (JSON, Markdown, CRM-ready). Use when researching prospects, preparing for sales calls, personalizing cold outreach, or building lead lists. Pairs perfectly with trawl for autonomous lead gen → enrichment → outreach pipelines.
As a process C 52/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches
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 52/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 3 mutating operations with no state check
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 87 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2875 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 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)
- +1No license
- +2Single-language instructions
- +3Description length 751: enough signal without eating the budget
- +4Structure: 18 headings
- +3Step-by-step instructions: 87 items
- +3Output format is stated explicitly
- +4Has examples (6 code blocks)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.