annotate

A skill for creating annotation workflows for AI applications. Annotation means labeling or marking useful information in raw AI logs and conversation transcripts.

In plain words
What is it for?
Exploring logs and transcripts, extracting evaluation data, and setting up language-model-based judging.
Why use it?
It helps turn unstructured agent records into evaluation data and supports creating an AI judge to assess results.

Skill for Claude CodeCodex

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/haizelabs/annotate/annotate_skill
Any agent
npx skills add haizelabs/annotate --skill annotate_skill
Clone the repo
git clone --depth 1 https://github.com/haizelabs/annotate

Made for: Claude Code, Codex.

Per session 38 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,925 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 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 $0.00038 $0.03925
Opus 5 $0.00019 $0.01962
Sonnet 5 $0.00008 $0.00785
Haiku 4.5 $0.00004 $0.00392

Measured 2d ago against content hash c4f75aeeab70, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

annotate scanned grade B with 2 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.

The scan reads SKILL.md. This mod also ships 15 executable files (__init__.py, frontend/eslint.config.js, frontend/postcss.config.js, …), 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

curl -s -X POST "http://localhost:8000/feedback-config" -H "Content-Type: application/json" -d @.haize_annotations/new_config.json

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

**REQUIRED STEP:** Call `curl -s http://localhost:8000/openapi.json` to get documentation on interacting with the FastAPI server.
annotate_skill/SKILL.md · 328 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Files

What ships with it

60 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. 2d ago First seen · 328 lines · 38 tokens per session scan B c4f75aeeab70

Subscribe to this mod's changes

annotate is a skill published in the GitHub repository haizelabs/annotate (17 stars, last pushed 10mo ago), with no licence file. It adds 38 tokens to every session and 3,925 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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