Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add realjaymes/marketingagentskills --skill skill-to-promptgit clone --depth 1 https://github.com/realjaymes/marketingagentskillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/realjaymes/marketingagentskills/skill-to-prompt)<a href="https://agentmods.dev/skills/realjaymes/marketingagentskills/skill-to-prompt"><img src="https://agentmods.dev/badge/skills/realjaymes/marketingagentskills/skill-to-prompt/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/realjaymes/marketingagentskills/skill-to-prompt"><img src="https://agentmods.dev/badge/skills/realjaymes/marketingagentskills/skill-to-prompt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 96 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.03147 |
| Opus 5 | $0.00030 | $0.01573 |
| Sonnet 5 | $0.00012 | $0.00629 |
| Haiku 4.5 | $0.00006 | $0.00315 |
Grade A, and why
skill-to-prompt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 364 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill to Prompt Converter
Converts a Claude skill (SKILL.md + references/) into ChatGPT Project format: one prompt instruction document (.docx, under 8,000 characters) and one knowledge file document (.docx).
What This Produces
For each conversion:
- Prompt Instructions (.docx) — The text that gets pasted into ChatGPT's "Instructions" field. Under 8,000 characters. Structured using the 9-component prompt formula.
- Knowledge File (1 .docx file) — Uploaded to the ChatGPT Project as reference material. Contains all detailed workflows, templates, frameworks, examples, and reference content consolidated into a single document.
All .docx files follow standard formatting: Arial font, 10pt normal text, H1=20pt, H2=16pt, H3=14pt, H4=12pt, 1.15 line spacing.
Conversion Workflow
Step 1: Locate and Read Source Skill
If user provides a skill name (e.g., "copywriting"):
- Look in
~/.claude/skills/[skill-name]/SKILL.md
If user provides a path, use it directly.
Read everything:
SKILL.md(full content)- All files in
references/folder - Note any
scripts/orassets/folders (these need special handling)
Step 2: Analyze Skill Complexity
Count total source content to understand how much compression is needed for the single knowledge file:
| Complexity | Criteria | Compression Needed |
|---|---|---|
| Simple | <300 lines in SKILL.md, no reference files | Minimal — content fits easily in one knowledge file |
| Medium | 300-500 lines or 1-2 reference files | Moderate — condense verbose sections, keep all frameworks and examples |
| Complex | 500+ lines or 3+ reference files | Heavy — prioritize frameworks, worked examples, and actionable content. Summarize repetitive sections |
Regardless of complexity, always produce exactly 1 knowledge file.
Step 3: Map Content to the 9-Component Prompt Formula
Read references/prompt-structure-guide.md for the full mapping guide.
Extract from the Claude skill and map to ChatGPT instruction components:
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 364 lines · 61 tokens per session scan A 4631cd1eef09
skill-to-prompt is a skill published in the GitHub repository realjaymes/marketingagentskills (59 stars, last pushed 2d ago), licensed MIT. It adds 61 tokens to every session and 3,147 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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