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 celticht32/Couchbase-Skills-for-Claude.ai --skill couchbase-sizinggit clone --depth 1 https://github.com/celticht32/Couchbase-Skills-for-Claude.aiWrote 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/celticht32/couchbase-skills-for-claude.ai/couchbase-sizing)<a href="https://agentmods.dev/skills/celticht32/couchbase-skills-for-claude.ai/couchbase-sizing"><img src="https://agentmods.dev/badge/skills/celticht32/couchbase-skills-for-claude.ai/couchbase-sizing/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/celticht32/couchbase-skills-for-claude.ai/couchbase-sizing"><img src="https://agentmods.dev/badge/skills/celticht32/couchbase-skills-for-claude.ai/couchbase-sizing.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 | $0.00195 | $0.01958 |
| Opus 5 | $0.00097 | $0.00979 |
| Sonnet 5 | $0.00039 | $0.00392 |
| Haiku 4.5 | $0.00019 | $0.00196 |
Grade A, and why
couchbase-sizing 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Couchbase sizing & capacity planning
A skill for numerical planning of Couchbase deployments. Companion to couchbase-mcp (which operates clusters) and couchbase-data-modeling (which designs the data shape) — this skill answers "how much" and "how many."
When this skill applies
Use this skill whenever the conversation involves estimating resources or capacity:
- "How much RAM do I need?"
- "How many nodes for X documents?"
- "Which Capella tier should I use?"
- "Will this fit in 32 GB?"
- "Should I scale up or scale out?"
- "How big will the index be?"
- "What replica count?"
- "Sizing for vector search"
- "How much XDCR bandwidth"
- "Capacity for next year's growth"
If the conversation is about what to store (modeling), use couchbase-data-modeling. If it's about how to operate (calling tools), use couchbase-mcp. This skill is purely about resource math.
Pick the right reference
| Question | Read |
|---|---|
| "How much RAM / what's the working set?" | references/memory.md |
| "How many nodes? What replica count?" | references/nodes.md |
| "How much disk / storage?" | references/disk.md |
| "Network bandwidth, XDCR throughput?" | references/network.md |
| "How big will the GSI / FTS / vector index be?" | references/indexes.md |
| "Which Capella tier?" | references/capella.md |
| "Read-heavy vs write-heavy vs vector vs time-series sizing?" | references/workload-shapes.md |
What you need from the user before sizing anything
Sizing math depends on workload data. Without these inputs, the best you can do is order-of-magnitude estimates with explicit assumptions. Ask the user for any of these that aren't already in context:
- Document count at present, and expected growth rate (per month or year)
- Average document size (and if it varies a lot, the 95th percentile too)
- Reads per second (peak, not average — sizing is for peak)
- Writes per second (peak)
- Working set assumption: what fraction of documents are "hot" (accessed regularly)? Common: 20%, 50%, 100%
- Replica count target (usually 1 or 2)
- Services needed (Data, Query, Index, FTS, Eventing, Analytics, Backup, Search)
- TTL / retention (does data age out?)
What ships with it
7 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 · 140 lines · 195 tokens per session scan A de241c3efc1c
couchbase-sizing is a skill published in the GitHub repository celticht32/Couchbase-Skills-for-Claude.ai (4 stars, last pushed 2mo ago), licensed MIT. It adds 195 tokens to every session and 1,958 once invoked, about $0.0010 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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