Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/adaptocms/adapto-cms-agent-skillsnpx agentmods add skills/adaptocms/adapto-cms-agent-skills/adapto-content-researchWrote 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/adaptocms/adapto-cms-agent-skills/adapto-content-research)<a href="https://agentmods.dev/skills/adaptocms/adapto-cms-agent-skills/adapto-content-research"><img src="https://agentmods.dev/badge/skills/adaptocms/adapto-cms-agent-skills/adapto-content-research/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/adaptocms/adapto-cms-agent-skills/adapto-content-research"><img src="https://agentmods.dev/badge/skills/adaptocms/adapto-cms-agent-skills/adapto-content-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00065 | $0.01321 |
| Opus 5 | $0.00032 | $0.00660 |
| Sonnet 5 | $0.00013 | $0.00264 |
| Haiku 4.5 | $0.00006 | $0.00132 |
Grade A, and why
adapto-content-research 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 12d 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
adapto:content-research
The first step of the content pipeline (content-pipeline.md). It
researches what's worth writing — grounded in the project brain — and produces a dated research
dossier the planning step turns into a content slate. It fans out adapto-researcher subagents across
angles, proactively pulls in your own data, and reads the ledger so it never re-researches covered
ground. No CMS writes — safe and re-runnable.
Autonomous-safe (studio.md §4): local, no CMS writes — an autonomous cycle can run this unattended; the cycle parks at the human gate before
adapto:content-upload.
When to use
- "Research content ideas", "what should we write about", "do content research", "look at competitor X".
- Start of a content cycle, after the brain exists (
adapto:project-define).
When not to use
- Turning research into a plan/slate →
adapto:content-plan. - Writing drafts →
adapto:content-create. - Consolidating learnings into the brain →
adapto:project-learn.
Inputs
- The brain (
.adapto/project/: identity, audience, pillars, seo, competitors, inventory). - Your data, proactively requested — ask up front: "drop any Search Console exports, keyword lists, or
analytics into
.adapto/sources/and I'll treat them as ground truth." (conventions.md §16) - URLs you provide — competitor pages or interesting web content to factor in.
- The ledger (
.adapto/ledger.json) — to skip already-covered/planned topics. - Optional: a connected SEO-data MCP (used automatically if present; never required).
Outputs
- A dated dossier
.adapto/research/<YYYY-MM-DD>-<topic>.md: findings by angle (cited), a keyword/intent map, competitor gaps, and a menu of content opportunities for planning. - Additive enrichment of
seo.md/competitors.md/inventory.md(append new findings — never rewrite; deliberate consolidation isadapto:project-learn's job) and a datedlearnings.mdentry. - Next step:
adapto:content-plan— turn the dossier into a cycle slate of briefs.
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.
- 12d ago First seen · 82 lines · 65 tokens per session scan A cd2272e80311
adapto-content-research is a skill published in the GitHub repository adaptocms/adapto-cms-agent-skills (1 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 1,321 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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