What is port-context-lake?

A design guide for building a Port context lake: a connected data model of software and business objects, their properties, and their relationships. Port is a platform for organizing this information so agents and workflows can use it.

Use it to decide which Port blueprints to create, how they should relate, and how mirror or summary fields should connect information across the model.

It helps replace a flat software catalog with connected information that can be searched, followed, and used for actions.

port-context-lake — Skill for Claude Code by port-labs

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 port-labs/port-skills --skill port-context-lake

Clone the repo

git clone --depth 1 https://github.com/port-labs/port-skills

Made for: Claude Code.

Or install port-skills, the plugin that ships this one along with the rest of its 10 skills, 1 command, 2 MCP servers.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/port-labs/port-skills/port-context-lake/github.svg)](https://agentmods.dev/skills/port-labs/port-skills/port-context-lake)

Your own site

<a href="https://agentmods.dev/skills/port-labs/port-skills/port-context-lake"><img src="https://agentmods.dev/badge/skills/port-labs/port-skills/port-context-lake/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/port-labs/port-skills/port-context-lake"><img src="https://agentmods.dev/badge/skills/port-labs/port-skills/port-context-lake.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 115 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,423 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.

Model	Per session	Once invoked
Fable 5.1	$0.00115	$0.01423
Opus 5	$0.00057	$0.00711
Sonnet 5	$0.00023	$0.00285
Haiku 4.5	$0.00012	$0.00142

Measured 12d ago against content hash 422a0f4edbd7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

port-context-lake 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.

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.

skills/port-context-lake/SKILL.md · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build a context lake

A context lake is Port's data model once it stops being a flat catalog and becomes a connected graph: blueprints related to each other, with mirror and aggregation properties, descriptions, and relation titles precise enough that an AI agent can traverse it and act, not just browse it. This skill designs that model. For the JSON mechanics of any single blueprint, property, or relation, use port-blueprints; this skill is the layer above that: what to build, in what order, and why.

Prerequisites

Go over the port-getting-started skill first if this is your first time working with Port, it covers signing up and connecting Port's MCP server.
If Port's MCP server is connected, this skill can use it to check what already exists (list_blueprints) and apply the resulting blueprint, relation, and property changes directly (upsert_blueprint), rather than just handing you JSON to apply yourself. Search search_port_knowledge_sources for anything this skill doesn't cover.

How to build it

Start from what Port already gives you. Every account ships built-in blueprints (_user, _team, _scorecard, and others) that you extend, not replace. See references/default-blueprints.md.
Design the core layer before the provider layer. Model your organization's own shape first (organization, team, service), then relate it to provider-specific blueprints your integrations create (GitHub, GitLab, Jira, ...), rather than duplicating provider data into your core blueprints. See references/reference-architecture.md for a full worked example.
Model hierarchy with a self-relation, not one blueprint per tier. A parent_team relation on _team handles arbitrary org depth. See references/relations-and-hierarchy.md.
Use ownership instead of a custom team relation. Port's built-in $team field already rolls up into _team aggregations for free. See references/ownership.md.
Add mirror and aggregation properties, not duplicated data. Mirror a single related value onto its source; aggregate across many related entities on the blueprint that sits above them. For the JSON shape, see port-blueprints' references/calculation-properties.md; for which one to use and where to put it, see references/mirror-vs-aggregation.md.
Write it as an ontology, not a schema. Descriptions, relation titles, and typed properties are what let an agent understand the graph instead of just enumerating it. See references/ontology.md.
Decide integration vs. MCP connector per data source. Only data that needs relations, ownership, or scorecards belongs in the lake as ingested entities; everything else can stay a live MCP fetch. See references/ingestion-strategy.md.

Read the full file on GitHub · 96 lines

Files

What ships with it

10 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.

12d ago First seen · 96 lines · 115 tokens per session scan A 422a0f4edbd7

Subscribe to this mod's changes

port-context-lake is a skill published in the GitHub repository port-labs/port-skills (3 stars, last pushed 10d ago), licensed MIT. It adds 115 tokens to every session and 1,423 once invoked, about $0.0006 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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