AD lemlist
Official Lemlist API integration for sales automation and multichannel outreach. Use this skill when users want to: - Manage campaigns (create, list, pause, start, get stats) - Add, update, or remove leads from campaigns - Send messages via email, LinkedIn, WhatsApp, or SMS through inbox - Set up and manage webhooks for campaign events - Configure schedules for campaign sending - Manage unsubscribes (emails and domains) - Export campaign data (leads, activities, contacts) - Enrich leads with additional data - Control Lemwarm email warming - Work with sequences and steps - Manage inbox labels and conversations Examples: "list my lemlist campaigns", "add a lead to my campaign", "pause my campaign", "show campaign stats", "set up a webhook for email opens", "export my leads"
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
frontmatter-keyunknown frontmatter key "primaryEnv"
Process rating: all ten parameters 41/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 10 mutating operations with no state check
- 40Consistency. Frontmatter name (lemlist) differs from the folder (lemlist-official)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 12 steps
- 100Execution cost. Instruction body is 1119 tokens
- 100Progress reporting. Reports progress
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 782: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.