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 rules/kontent-ai/mcp-server/kontent-tool-descriptionsgit clone --depth 1 https://github.com/kontent-ai/mcp-serverWrote 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/rules/kontent-ai/mcp-server/kontent-tool-descriptions)<a href="https://agentmods.dev/rules/kontent-ai/mcp-server/kontent-tool-descriptions"><img src="https://agentmods.dev/badge/rules/kontent-ai/mcp-server/kontent-tool-descriptions.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00335 |
| Opus 5 | $0.00000 | $0.00168 |
| Sonnet 5 | $0.00000 | $0.00067 |
| Haiku 4.5 | $0.00000 | $0.00034 |
Grade A, and why
kontent-tool-descriptions 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 5d 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.
What it actually says
When creating or modifying MCP tool descriptions, follow this standardized pattern:
Template: "[Action] [Kontent.ai entity] [method/context]"
Required Elements:
-
Always include "Kontent.ai" explicitly in the description
-
Action verbs: Use consistent verbs like:
- Create (add)
- Get / Retrieve
- Update (modify/edit) — for patch tools
- Delete (remove)
- List / Find / Filter
- Search — for semantic/AI search
-
Entity specification: Clearly identify the Kontent.ai entity:
- content type, content type snippet, content item, content item variant
- asset, taxonomy group, workflow, language, space, collection
- Use "ID" for identifiers (not "internal ID")
Examples:
✅ Good:
- "Retrieve Kontent.ai content type by ID"
- "Create (add) new Kontent.ai content item"
- "Create Kontent.ai content item variant — translate and localize content"
- "Update (modify/edit) Kontent.ai content type schema using patch operations"
❌ Bad:
- "Get content type by ID" (missing Kontent.ai)
- "Add content type" (missing Kontent.ai, use "Create")
- "Retrieve item" (too vague, missing Kontent.ai)
- "Get Kontent.ai content type by internal ID" (don't use "internal ID", just "ID")
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.
- 5d ago First seen · 38 lines · 0 tokens per session scan A e2b24f95b16e
kontent-tool-descriptions is a cursor rule published in the GitHub repository kontent-ai/mcp-server (9 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 335 tokens. 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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