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 Infrasity-Labs/dev-gtm-claude-skills --skill content-briefgit clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsWrote 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/infrasity-labs/dev-gtm-claude-skills/content-brief)<a href="https://agentmods.dev/skills/infrasity-labs/dev-gtm-claude-skills/content-brief"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/content-brief/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/infrasity-labs/dev-gtm-claude-skills/content-brief"><img src="https://agentmods.dev/badge/skills/infrasity-labs/dev-gtm-claude-skills/content-brief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00157 | $0.02644 |
| Opus 5 | $0.00078 | $0.01322 |
| Sonnet 5 | $0.00031 | $0.00529 |
| Haiku 4.5 | $0.00016 | $0.00264 |
Grade A, and why
content-brief 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 9d 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Brief — Keyword-to-Notion Brief Generator
Generates a structured SEO content brief from a target keyword. Output follows the mandatory Direction prompt format so the text_parser.py script can extract every field for Notion without manual cleanup.
Invocation Triggers
Explicit phrases (any of):
- "create a content brief for [keyword]"
- "brief this keyword: [keyword]"
- "content brief on [topic]"
- "generate a brief for [keyword]"
- "write a brief for [keyword]"
- "run the content brief skill"
Implicit signals:
- User provides a keyword and asks for an SEO spec, editorial spec, or writing assignment
- User pastes a keyword list and asks for briefs
When triggered, run immediately — no upfront intake beyond the keyword itself.
Grill-Me Intake (One Question, Optional)
Run the brief without questions when the keyword is clear.
Ask one clarifying question only when both are true:
- The target audience or client is not inferrable from context
- Audience changes the content angle meaningfully (e.g., "project management software" could target PMs or developers)
Quick clarification — who is the primary audience for "[keyword]"?
- [Inferred persona A — e.g., HR Director]
- [Inferred persona B — e.g., Operations Manager]
- Tell me
Why I'm asking: audience shapes the H1, content angle, and writer notes. One question prevents a wrong brief.
Max one question. If audience is inferable, skip and proceed.
Data Gathering (Before Writing the Brief)
Run these steps before generating the Direction prompt output:
Step 1 — Keyword Metrics
Preferred: Ahrefs MCP (keywords_explorer_overview) → volume, KD, CPC, SERP data.
Fallback (no Ahrefs MCP): Use WebSearch to estimate:
- Search
[keyword] search volume KD CPC site:ahrefs.com OR site:semrush.com OR site:moz.com - Extract available volume/KD/CPC estimates
- If no data found, set VOLUME/CPC/DIFFICULTY to
[not available — add manually]
Step 2 — Competitor H2/H3 Analysis
- WebSearch
[keyword]→ identify top 3 organic results (skip ads, maps, featured snippets) - WebFetch each URL → extract all H2 and H3 headings
- Note: competitor structure informs the H2_OUTLINE. Do not copy — use as gap analysis.
What ships with it
5 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.
- 9d ago First seen · 248 lines · 157 tokens per session scan A 0bc607563ee1
content-brief is a skill published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 157 tokens to every session and 2,644 once invoked, about $0.0008 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 2026-09-03.
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