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 skillmds/skillmd --skill ktxgit clone --depth 1 https://github.com/skillmds/skillmdWrote 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/skillmds/skillmd/ktx)<a href="https://agentmods.dev/skills/skillmds/skillmd/ktx"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/ktx/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/skillmds/skillmd/ktx"><img src="https://agentmods.dev/badge/skills/skillmds/skillmd/ktx.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 | $0.00081 | $0.02336 |
| Opus 5.5 | $0.00032 | $0.00934 |
| Sonnet 5.5 | $0.00016 | $0.00467 |
| Haiku 4.5 | $0.00008 | $0.00234 |
Grade A, and why
ktx 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.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ktx
Install and configure ktx, the open-source context layer for data agents. Use this skill when a user wants an agent to add ktx to a project, connect data sources, build initial context, install agent integration, or troubleshoot a local ktx setup.
Operating rules
- Act autonomously when the user asks you to install or configure ktx.
The non-interactive scripted flow below is the canonical path — bare
ktx setupis interactive (clack prompts) and an agent cannot drive it. - Setup's non-interactive flags are intentionally hidden from
--help. Use the flags listed below; verify uncommon flags against the docs athttps://docs.kaelio.com/ktx/or this skill — not against--helpoutput. - Ask only for values you cannot infer: project directory, connection targets, credentials, account identifiers, and source selections.
- Never ask the user to paste secrets when an
env:VAR_NAMEorfile:/pathreference would work. Pasting a literal URL is also safe —ktx setupauto-externalizes URLs into.ktx/secrets/<id>-url(see workflow step 2). - Do not commit
.ktx/secrets/*. - Print each command you run and its result.
- If a command fails, identify the cause and change something before retrying.
Gather inputs once
Before invoking ktx setup, collect in one round:
- Project directory (default: current working directory).
- LLM backend and key strategy. In
--no-inputmode the CLI defaults toanthropicand requires an API key. When the user is inside Claude Code, pass--llm-backend claude-codeexplicitly; otherwise pass--llm-backend anthropic --anthropic-api-key-env ANTHROPIC_API_KEY. - Embedding backend (
sentence-transformersis the local default and needs no key; useopenaionly if the user already has a key, then pass--embedding-api-key-env OPENAI_API_KEY). - Database: driver, connection id, URL (or
env:/file:ref), and one or more schemas. - Optional context sources (dbt, Metabase, Looker, LookML, MetricFlow,
Notion). Add each one with a follow-up
ktx setup --source …run (see Add context sources); use--skip-sourcesonly when the user has none.
What ships with it
1 file 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.
- 1mo ago First seen · 215 lines · 81 tokens per session scan A 036c49a32da6
ktx is a skill published in the GitHub repository skillmds/skillmd (143 stars, last pushed 4d ago), licensed MIT. It adds 81 tokens to every session and 2,336 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-09-19.
ktx compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| ktxskillmds/skillmd | Skill | 143 | 4d ago | MIT | A | 81 | Claude Code |
| glycobiologysynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 67 | Claude Code, Codex |
| shapsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 109 | Claude Code, Codex |
| cellxgene-censussynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 67 | Claude Code, Codex |
| esmsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 86 | Claude Code, Codex |
| llm-as-judge-evaluationsynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 56 | Claude Code, Codex |
| groq-inferencesynthetic-sciences/openscience | Skill | 4.4k | yesterday | Apache-2.0 | A | 77 | Claude Code, Codex |