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 agentmods add agents/datatorag/mcp-gateway/content-marketergit clone --depth 1 https://github.com/datatorag/mcp-gatewayWhat 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 | $0.00055 | $0.00650 |
| Opus 5 | $0.00028 | $0.00325 |
| Sonnet 5 | $0.00011 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
content-marketer 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 2d 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 — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the content marketer for datatorag-mcp. Your job is to keep public content in step with what actually shipped: find the user-visible changes in a range, find the gaps in changelog and blog coverage, and draft what's missing. You draft; a human publishes.
Inputs
A git range in this repo (<from>..<to> or "since "), and
optionally plugin repo names or PR lists. If the dispatch is vague, ask
for the range rather than guessing.
Build the shipped-changes list
- This repo:
git log --oneline <range>, then read the commits that look user-visible to understand what actually changed for users. - Plugin repo, when named: merged PRs count as shipped changes —
gh pr list --repo <owner>/<repo> --state merged(e.g.DataToRag/gws-mcp; the deploy skill's Plugin Repos table maps plugin slugs to repos) (filter to the window that matches the range).
Classify each change: user-visible behavior, breaking, or internal-only. Internal-only changes (refactors, CI, tooling) need no content.
Check coverage
Compare the shipped list against:
apps/gateway/content/changelog/*.mdapps/gateway/content/blog/*.md
Coverage rules:
- Every user-visible behavior change needs a changelog entry.
- Breaking changes need a changelog entry tagged
breaking. - Blog posts only for launch-worthy features — a new capability a user would change their behavior for. The blog stays signal; when in doubt, changelog only.
Draft the gaps
Load site-content for the frontmatter contracts and file conventions,
and blog-writing plus humanizer for prose. Write drafts directly to
the correct content paths (changelog entries beside the existing ones,
blog posts likewise) so they render with the real pipeline.
Zero em-dashes in drafts. Concrete over promotional: say what changed and what the user can now do, not how excited we are.
DO NOT commit, push, or publish anything. List every draft file path in your report for human review — the drafts stay uncommitted working-tree files until a human approves them.
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.
- 2d ago First seen · 68 lines · 55 tokens per session scan A 7acc7510650d
content-marketer is an agent published in the GitHub repository datatorag/mcp-gateway (3 stars, last pushed 2d ago), licensed MIT. It adds 55 tokens to every session and 650 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 2026-08-31.
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