filtering

filtering is a skill for Claude Code, Codex from onsi/ginkgo. It costs 117 tokens per session (1,768 once invoked), scanned A, original, MIT.

A guide to running only selected tests in a Ginkgo test suite. Ginkgo is a Go testing framework, and its filters include pending or skipped tests, labels, version constraints, names, and files.

In plain words
What is it for?
Use it to configure local test runs or continuous integration jobs that focus on particular tests, labels, files, versions, or development states.
Why use it?
It explains how several test-selection rules combine, including which rules take priority, so you can run the intended subset.

Skill for Claude CodeCodex

Part of the ginkgo plugin — 13 skills shipped together

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.

agentmods
npx agentmods add skills/onsi/ginkgo/filtering
Any agent
npx skills add onsi/ginkgo --skill filtering
Clone the repo
git clone --depth 1 https://github.com/onsi/ginkgo

Made for: Claude Code, Codex.

Or install ginkgo, the plugin that ships this one along with the rest of its 13 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 filtering

README.md
[![agentmods](https://agentmods.dev/badge/skills/onsi/ginkgo/filtering.svg)](https://agentmods.dev/skills/onsi/ginkgo/filtering)
Your own site
<a href="https://agentmods.dev/skills/onsi/ginkgo/filtering"><img src="https://agentmods.dev/badge/skills/onsi/ginkgo/filtering.svg" alt="Measured on agentmods" height="20"></a>
Per session 117 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,768 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00117 $0.01768
Opus 5 $0.00059 $0.00884
Sonnet 5 $0.00023 $0.00354
Haiku 4.5 $0.00012 $0.00177

Measured 4d ago against content hash 2c3e0be56fae, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

filtering 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 4d 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.

plugins/ginkgo/skills/filtering/SKILL.md · 119 lines

How it starts

The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Filtering specs: running a subset

Ginkgo offers many ways to run fewer specs — ad-hoc (Pending/Skip/Focus) and structured (labels, semver, file/description filters). They combine by a strict precedence (see bottom). Decorator specifics live in ginkgo:decorators; label-driven CI in ginkgo:ci. Docs: https://onsi.github.io/ginkgo/#filtering-specs.

Pending — compile-time skip, uncoercible

Marks a spec/container as under development. Nothing can override Pending and make it run — not focus, not labels.

It("needs work", Pending, func() { ... })
It("placeholder", Pending)            // pending specs need no closure
PDescribe("not ready", func() { ... }) // == Describe(..., Pending); X-prefix is identical
PIt(...) / XIt(...) / PEntry(...)

Pending specs don't fail the suite. ginkgo --fail-on-pending makes them fail CI — a policy that pending specs shouldn't be committed. Pending is compile-time only; you cannot make a spec pending at runtime — for that, use Skip.

Skip — runtime skip

Call Skip("reason") from any subject or setup node to skip during the run phase. It panics to halt the spec (like Fail) and records the reason; it does not fail the suite (even skipping every spec passes).

It("if it can", func() {
	if !someCondition { Skip("special condition wasn't met") }
	...
})

Scope matters: in a BeforeEach it skips the current spec; in a BeforeAll it skips all specs in the Ordered container; in a BeforeSuite it skips the entire suite. You cannot call Skip in a container body — it only applies during the run phase.

Focus — programmatic, for iterating (don't commit it)

When any spec is focused, Ginkgo runs only focused specs.

FIt("just me", func() { ... })   // or It(..., Focus, ...)
FDescribe(...) / FContext(...) / FEntry(...)

Child focus unfocuses focused ancestors. F an inner It inside an FDescribe and only that It runs — matches how you narrow while debugging.

Read the full file on GitHub · 119 lines

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. 4d ago First seen · 119 lines · 117 tokens per session scan A 2c3e0be56fae

Subscribe to this mod's changes

filtering is a skill published in the GitHub repository onsi/ginkgo (9,050 stars, last pushed 24d ago), licensed MIT. It adds 117 tokens to every session and 1,768 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 2026-08-30.

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