analyze

A Kubernetes issue classifier that extracts technical clues from a GitHub issue. Kubernetes is software for running and managing containers across machines; a SIG is one of its specialized contributor groups, which this add-on does not identify.

In plain words
What is it for?
Use it to identify the affected Kubernetes component or area from an issue title and body. Its output can support a later step that assigns the issue to the appropriate group.
Why use it?
It turns a long issue description into the technical signals needed for later routing. It avoids guessing which Kubernetes contributor group owns the issue.

Agent

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 agents/tgpski/leather/analyze
Clone the repo
git clone --depth 1 https://github.com/TGPSKI/leather
Per session 2 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 181 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown 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 $0.00002 $0.00181
Opus 5 $0.00001 $0.00090
Sonnet 5 $0.00000 $0.00036
Haiku 4.5 $0.00000 $0.00018

Measured 2d ago against content hash a2a129ad1e46, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyze 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 2d 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.

examples/14-sig-triage/agents/analyze.agent.md · 22 lines

The source is not reproduced here

Licensed GPL-3.0

The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.

Read it on GitHub

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. 2d ago First seen · 22 lines · 2 tokens per session scan A a2a129ad1e46

Subscribe to this mod's changes

analyze is an agent published in the GitHub repository TGPSKI/leather (17 stars, last pushed 23d ago), licensed GPL-3.0. It adds 2 tokens to every session and 181 once invoked, about $0.0000 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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