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/vfarcic/dot-ainpx agentmods add skills/vfarcic/dot-ai/write-docsWrote 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/vfarcic/dot-ai/write-docs)<a href="https://agentmods.dev/skills/vfarcic/dot-ai/write-docs"><img src="https://agentmods.dev/badge/skills/vfarcic/dot-ai/write-docs/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/vfarcic/dot-ai/write-docs"><img src="https://agentmods.dev/badge/skills/vfarcic/dot-ai/write-docs.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 | $0.00032 | $0.01624 |
| Opus 5.5 | $0.00013 | $0.00650 |
| Sonnet 5.5 | $0.00006 | $0.00325 |
| Haiku 4.5 | $0.00003 | $0.00162 |
Grade A, and why
write-docs 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 1mo 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.
This is a copy
98% identical to dot-ai-write-docs — 33 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Write Documentation
Write accurate, user-focused documentation with real examples by executing operations through the user.
Principles
- Execute-then-document: Never write examples without real output
- Chunk-by-chunk: Write one section at a time, get confirmation before proceeding
- User-focused: Write for users, not developers
- Validate prerequisites: Run setup steps from existing docs to verify they work
- Claude runs infrastructure, user runs MCP: Claude executes all bash/infrastructure commands. Only ask user for MCP client interactions (the actual user-facing examples).
- Fix docs when broken: If existing docs don't work during setup, STOP and discuss updating those docs before proceeding.
Workflow
Step 1: Identify the Documentation Target
Ask the user what documentation to write. Options:
- New feature guide (e.g., "knowledge base guide")
- Update existing guide
- API reference
- Setup/configuration guide
Step 2: Fresh Environment Setup
ALWAYS start with a clean test cluster to ensure reproducible documentation.
Follow the actual docs (docs/setup/mcp-setup.md) - this validates they work.
Claude executes all infrastructure steps directly using Bash tool:
-
Tear down existing test cluster if present
kind delete cluster --name dot-ai-test 2>/dev/null || true rm -f ./kubeconfig.yaml -
Create fresh Kind cluster with local kubeconfig
kind create cluster --name dot-ai-test --kubeconfig ./kubeconfig.yaml export KUBECONFIG=./kubeconfig.yaml -
Install prerequisites (ingress controller)
kubectl apply -f https://raw.githubusercontent.com/kubernetes/ingress-nginx/main/deploy/static/provider/kind/deploy.yaml # Wait for ingress to be ready kubectl wait --namespace ingress-nginx --for=condition=ready pod --selector=app.kubernetes.io/component=controller --timeout=300s -
Follow docs/setup/mcp-setup.md (skip controller if not needed for the feature)
- Step 1: Set environment variables (use existing API keys from env)
- Step 2: Install controller via Helm (skip if feature doesn't need it)
- Step 3: Install MCP server via Helm
- Step 4: Tell user to configure MCP client
- Step 5: Tell user to verify with "Show dot-ai status"
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.
- 1mo ago First seen · 182 lines · 32 tokens per session scan A b5b587251217
write-docs is a skill published in the GitHub repository vfarcic/dot-ai (337 stars, last pushed yesterday), licensed MIT. It adds 32 tokens to every session and 1,624 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to dot-ai-write-docs, differing in 33 lines, and is treated as a copy.
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