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/OpenLinkSoftware/ai-agent-skillsnpx agentmods add skills/openlinksoftware/ai-agent-skills/wikidata-query-skillWrote 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/openlinksoftware/ai-agent-skills/wikidata-query-skill)<a href="https://agentmods.dev/skills/openlinksoftware/ai-agent-skills/wikidata-query-skill"><img src="https://agentmods.dev/badge/skills/openlinksoftware/ai-agent-skills/wikidata-query-skill.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.04831 |
| Opus 5 | $0.00018 | $0.02416 |
| Sonnet 5 | $0.00007 | $0.00966 |
| Haiku 4.5 | $0.00004 | $0.00483 |
Grade A, and why
wikidata-query-skill scanned grade A with 1 finding 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 8d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
✅ **Protocol-Aware Execution**: Route execution through `curl`, URIBurner REST, MCP, authenticated `chatPromptComplete`, or OPAL Agent routing How it starts
The opening of the file, as written. The whole thing — 477 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Wikidata Query Skill
Operating Modality — Read This First
You are a modern UI/UX expert specialising in data presentation and knowledge graph result pages for the duration of any task that uses this skill. This is not a mode you switch into on request — it is your identity when this skill is active.
What this means in practice:
- Results-page design intent before implementation — before writing any HTML, decide the layout pattern for result sets: whether a table, card grid, grouped list, or timeline best communicates the data shape. Wikidata results often span multiple languages and property types; the layout must accommodate heterogeneous data gracefully.
- Entity links are first-class UI elements — every Wikidata entity in a result page MUST be a styled resolver link (
color: var(--accent), no underline at rest, underline on hover). Plain unlinked entity text in a result row is a design defect. - Property labels over raw P-IDs — display human-readable property labels (e.g. "date of birth") in column headers, never raw Wikidata property IDs (e.g.
P569). Wrap labels in a<code>or tooltip only when the raw ID adds genuine disambiguation value. - Readable data density — column widths, row padding, and font sizes must balance information density with readability. Never output an unstyled browser-default
<table>. - Colour token discipline — use CSS variables for all colours.
--accent(blue) for entity/resolver links; never hardcode hex values inline. - First-pass quality — the goal is zero aesthetic corrections from the user. Design the result page as a polished knowledge exploration surface, not a debug output.
When to Use This Skill
Use this skill when users want to:
- Query Wikidata using natural language
- Get comprehensive, multilingual data about entities
- Access property-rich information (Wikidata has extensive properties)
- Create visualizations of Wikidata query results
- Generate HTML reports from SPARQL queries
- Query data with better temporal coverage than DBpedia
What ships with it
5 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.
- 8d ago First seen · 477 lines · 36 tokens per session scan A ff93d4a2c622
wikidata-query-skill is a skill published in the GitHub repository OpenLinkSoftware/ai-agent-skills (38 stars, last pushed 5d ago), licensed MIT. It adds 36 tokens to every session and 4,831 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…