gateway-plugin-datakit

gateway-plugin-datakit is a skill for Claude Code from Kong/ai-marketplace. It costs 57 tokens per session (1,321 once invoked), scanned A, original, MIT.

A guide for designing and debugging Kong DataKit plugin flows. Kong DataKit is a system for arranging request and response processing as connected steps, including data transformations and stored values.

In plain words
What is it for?
Use it to build or debug flows with node selection, directed graphs, jq data transformations, caching, vault values, and phase-specific request or response handling.
Why use it?
It helps identify the right processing phase, step types, connections, and data shapes for a DataKit flow. It keeps troubleshooting focused on DataKit behavior instead of unrelated Kong configuration tools.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the kong-konnect plugin — 21 skills shipped together

Good fit Use it to build or debug flows with node selection, directed graphs, jq data transformations, caching, vault values, and phase-specific request or response handling.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kong/ai-marketplace/gateway-plugin-datakit
Install

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.

Any agent
npx skills add Kong/ai-marketplace --skill gateway-plugin-datakit
Clone the repo
git clone --depth 1 https://github.com/Kong/ai-marketplace

Made for: Claude Code.

Or install kong-konnect, the plugin that ships this one along with the rest of its 21 skills.

Wrote 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.

agentmods badge for gateway-plugin-datakit

README.md
[![agentmods](https://agentmods.dev/badge/skills/kong/ai-marketplace/gateway-plugin-datakit/github.svg)](https://agentmods.dev/skills/kong/ai-marketplace/gateway-plugin-datakit)
Your own site
<a href="https://agentmods.dev/skills/kong/ai-marketplace/gateway-plugin-datakit"><img src="https://agentmods.dev/badge/skills/kong/ai-marketplace/gateway-plugin-datakit/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.

agentmods 80×15 button for gateway-plugin-datakit

Your own site · 80×15
<a href="https://agentmods.dev/skills/kong/ai-marketplace/gateway-plugin-datakit"><img src="https://agentmods.dev/badge/skills/kong/ai-marketplace/gateway-plugin-datakit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,321 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00057 $0.01321
Opus 5 $0.00028 $0.00660
Sonnet 5 $0.00011 $0.00264
Haiku 4.5 $0.00006 $0.00132

Measured 12d ago against content hash cc0f0f7fe5d2, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

gateway-plugin-datakit 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 12d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_datakit_flow.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

plugins/kong-konnect/skills/gateway-plugin-datakit/SKILL.md · 135 lines

How it starts

The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Goal

Help the agent turn an orchestration request into a correct DataKit flow, or debug an existing flow, without drifting into generic Gateway or declarative tool guidance.

Own DataKit reasoning: phase choice, node selection, DAG structure, connection shape, cache or vault requirements, and debug strategy.

Tool Selection

Prefer working from the artifact that already owns the flow:

  • If the repo already contains DataKit YAML under deck, kong.yaml, or other declarative config, edit that artifact in place.
  • If the request depends on current Konnect state and kong-konnect MCP is available, use it to inspect the attached plugin instance and confirm whether the problem is in the saved config or only in the repo copy.
  • If the request is only about DataKit flow behavior, stay in this skill. Hand off only when the work becomes mainly about decK, kongctl, or Terraform packaging.

References To Load

Load only the file that matches the current branch:

  • references/node-reference.md
    • Load when choosing node types, checking required fields, or confirming what a node or implicit object can read or write.
  • references/patterns.md
    • Load when translating a user workflow into a starter flow shape such as fan-out merge, auth injection, caching, XML conversion, dynamic URLs, or header mutation.
  • references/resources-and-debugging.md
    • Load when the problem depends on cache or vault resources, live debug traces, deployment topology, or version-gated behavior.

Run scripts/validate_datakit_flow.py when a local YAML file already exists and you need deterministic checks for node naming, references, branch targets, cycles, implicit-field misuse, or missing cache or vault resources.

Workflow

  1. Classify the request before drafting YAML.
    • Identify whether the flow runs in access or response phase.
    • Confirm whether the plugin should mutate service_request, mutate response, or short-circuit with exit.
    • Confirm the attachment boundary: service, route, consumer, consumer group, or global.

Read the full file on GitHub · 135 lines

Files

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.

Changes

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.

  1. 12d ago First seen · 135 lines · 57 tokens per session scan A cc0f0f7fe5d2

Subscribe to this mod's changes

gateway-plugin-datakit is a skill published in the GitHub repository Kong/ai-marketplace (5 stars, last pushed 22d ago), licensed MIT. It adds 57 tokens to every session and 1,321 once invoked, about $0.0003 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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