BB email-lead-gen
OpenClaw Email Lead Generation — the complete outreach and pipeline system for your agent. Guided setup builds your config, Template Forge creates custom email sequences from a voice interview, and 3-tier architecture scales from manual pipeline tracking to fully automated cron-driven outreach. Add leads, score them, run email sequences, monitor replies, get morning briefings, and track your entire funnel — all through conversation. v1.0.1: timezone support, per-domain rate limits, email warmup, compliance/unsubscribe, audit logging, inbound HTML stripping, credential security, temp-file email body (fixes JSON escaping). Works standalone or alongside AI Persona OS. Built by Jeff J Hunter.
As a process B 67/100 · Nearly there — weak spots: when it triggers, consistency, execution cost
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 11813 tokens (recommended < 5000); move details to references/ - note
frontmatter-keyunknown frontmatter key "homepage"
Process rating: all ten parameters 67/100
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (email-lead-gen) differs from the folder (openclaw-email-lead-generation)
- 40Execution cost. Instruction body is 11813 tokens: crowds the task out of the window
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 99 steps, 1 vague phrases
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Failures and branches. 12 branches, has a failure section
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 29 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)
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 697: enough signal without eating the budget
- +4Structure: 45 headings
- +3Step-by-step instructions: 99 items
- +3Output format is stated explicitly
- +4Has examples (23 code blocks)
- +4Reference files are cited in the instructions (1 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.