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CC email-outreach

Writes personalized cold emails to new prospects: researches each one against the ideal customer profile, never contacts anyone twice, and queues drafts for approval. Use whenever someone wants cold emails, prospecting, or outreach to people who don't know them yet, even a handful. Not for existing clients; opted-in subscribers are email-sequence.

marcosmodly/marketing-skill Agent Skills author: marcosmodly 1 file body ≈ 6 858 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Writes personalized cold emails to new prospects: researches each one against the ideal customer profile, never contacts anyone twice, and queues drafts for…

As a process C 61/100 · Has gaps — References files that are not bundled: references/brand-voice.md, references/outreach-strategy.md

GeneratorGmailSales and CRMtype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
C
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
61/100
Has gaps
References files that are not bundled: references/brand-voice.md, references/outreach-strategy.md
Tools and files w 18
0
Inputs and preconditions w 11
0
Result and completion w 14
60
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.
  2. The text references files that are not there: add them or drop the references.
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: 1. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6858 tokens (recommended < 5000); move details to references/
  • warning missing-ref reference to a missing file: references/brand-voice.md
  • warning missing-ref reference to a missing file: references/outreach-strategy.md

Process rating: all ten parameters 61/100

Will not run. References files that are not bundled: references/brand-voice.md, references/outreach-strategy.md
  • 0Tools and files. 2 referenced file(s) missing: references/brand-voice.md, references/outreach-strategy.md
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 60Result and completion. Output format stated, no completion criterion
  • 70Execution cost. Instruction body is 6858 tokens
  • 85Steps. 66 steps, 1 vague phrases
  • 100When it triggers. States when to use and when not to
  • 100Failures and branches. 9 branches, has a failure section
  • 100Consistency. Name and required fields are in place
  • 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

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
  • +1No license
  • +2Single-language instructions
  • +4Description says when NOT to use the skill
  • +3Description length 349: enough signal without eating the budget
  • +4Structure: 7 headings
  • +3Step-by-step instructions: 66 items
  • +3Output format is stated explicitly
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.