Apache TinkerPop is a graph-computing framework for applications that store or analyze connected data, such as property graphs in databases. Developers use its Gremlin traversal language, drivers, servers, and tools to work with different graph systems through a common interface.
Borrowing it
Nothing to install: this file belongs to apache/tinkerpop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/apache/tinkerpop/master/.skills/tinker-doc/SKILL.mdgit clone --depth 1 https://github.com/apache/tinkerpopWrote 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/apache/tinkerpop/tinker-doc)<a href="https://agentmods.dev/skills/apache/tinkerpop/tinker-doc"><img src="https://agentmods.dev/badge/skills/apache/tinkerpop/tinker-doc/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/apache/tinkerpop/tinker-doc"><img src="https://agentmods.dev/badge/skills/apache/tinkerpop/tinker-doc.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 63 Skill instructs the agent to never refuse or to always comply. Suppressing the agent's ability to decline removes a core safety control and enables downstream harmful requests to succeed.Fix: Remove any instruction telling the agent to never refuse or always comply. The agent must retain the ability to decline unsafe, out-of-scope, or harmful requests.
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 | $0.00096 | $0.02072 |
| Opus 5.5 | $0.00038 | $0.00829 |
| Sonnet 5.5 | $0.00019 | $0.00414 |
| Haiku 4.5 | $0.00010 | $0.00207 |
Grade A, and why
tinker-doc 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TinkerPop Documentation Skill
This skill is about the craft of TinkerPop documentation: getting the voice, audience, and shape of each kind of document right. The mechanics that keep the build green (executable code blocks, AsciiDoc wiring) are covered in the references and matter, but they serve the writing, not the other way around.
All project documentation lives under docs/src/ and is AsciiDoc, never
Markdown. It is organized into several books, each with its own audience and
purpose. The four directories under docs/src/dev/ are themselves separate
books, not one:
| Book | Path | Audience | Purpose |
|---|---|---|---|
| Reference | docs/src/reference/ |
Users | The complete, authoritative description of every feature and step |
| Recipes | docs/src/recipes/ |
Users | Reusable problem→solution patterns for real tasks |
| Tutorials | docs/src/tutorials/ |
Users (learning) | Story-driven walkthroughs of a focused topic |
| Upgrade | docs/src/upgrade/ |
Users (upgrading) | Announces what changed in a release and how to adapt |
| Provider | docs/src/dev/provider/ |
Graph providers | Implementation guidance, provider policies, and the canonical Gremlin semantics |
| IO | docs/src/dev/io/ |
Providers and advanced users | The serialization formats (GraphBinary, GraphSON, GraphML, Gryo) |
| Developer | docs/src/dev/developer/ |
Contributors | Contributing, development environment, committer and release process |
| Future | docs/src/dev/future/ |
Contributors | Design proposals for planned or possible changes |
The full per-book voice guide, with grounded examples from the real docs, is in references/books-and-voice.md. Read it before writing in any book you have not written in before. The short version of each book's character:
- Upgrade announces. It tells a feature's story — what changed and why it
matters — and defers exhaustive detail to the reference docs via
See:rather than cataloging every edge case itself. A typical entry is short: a paragraph or two and one example. It frames past shortcomings positively and treats breaking changes as a priority. - Reference and Recipes instruct. They are the focal point for correct usage and established patterns: complete, user-friendly, and formal.
- Tutorials teach through a story but otherwise follow the Reference/Recipes style.
- Provider documents internals in the Reference/Recipes style. The
gremlin-semantics.asciidocfile is special and load-bearing (see below). - IO specifies the serialization formats in the same formal, complete style as Provider.
- Developer docs are internal notes, instructions and standard processes for contributors.
- Future holds design proposals for changes under consideration.
What ships with it
4 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.
- 1mo ago Changed · +13 lines 503a3b43acc2
- 2mo ago First seen · 142 lines · 96 tokens per session scan A 065ac44c06d7
tinker-doc is a skill published in the GitHub repository apache/tinkerpop (2,150 stars, last pushed today), licensed Apache-2.0. It adds 96 tokens to every session and 2,072 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
code-graph
This skill should be used when understanding code structure, finding dependencies between functions/classes, tracing call graphs, or exploring code relationships. Trigger phrases include 'code graph', 'call graph', 'who calls', 'what calls', 'find dependencies', 'code structure', 'inheritance', 'find paths'.
memgraph-storage-reviewer
Review code changes in Memgraph's storage layer, including MVCC, concurrency patterns, WAL, recovery, DDL operations, index/constraint management, delta chains, and skip list operations. Invoke for pull requests or changes to src/storage/v2/.
skill-feedback-writer
Use to identify missing instructions in another skill based on its output.
pr-comment-evaluator
Use to judge whether a PR review comment sounds polite.
graph-mutation-plan
Cookbook for composing an applygraphmutations plan — stable entitykey patterns, the canonical label/edge vocabulary, evidence/invalidation/confidence discipline, and a worked example. Load this when building a non-trivial mutation plan.
performing-cloud-asset-inventory-with-cartography
Perform comprehensive cloud asset inventory and relationship mapping using Cartography to build a Neo4j security graph of infrastructure assets, IAM permissions, and attack paths across AWS, GCP, and Azure.