field-notes

field-notes is a skill for Claude Code, Codex from Dragoon0x/taste-skills. It costs 42 tokens per session (343 once invoked), scanned A, original, MIT.

A template for recording structured observations about real products, including their intended experience, successful decisions, weaknesses, and underlying principles.

In plain words
What is it for?
Use it for product analyses, case studies, design references, and teaching examples after actually using the product.
Why use it?
It turns vague design impressions into specific notes that can be shared, searched, and used for learning.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for product analyses, case studies, design references, and teaching examples after actually using the product.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dragoon0x/taste-skills/field-notes
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 Dragoon0x/taste-skills --skill field-notes
Clone the repo
git clone --depth 1 https://github.com/Dragoon0x/taste-skills

Made for: Claude Code, Codex.

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 field-notes

README.md
[![agentmods](https://agentmods.dev/badge/skills/dragoon0x/taste-skills/field-notes/github.svg)](https://agentmods.dev/skills/dragoon0x/taste-skills/field-notes)
Your own site
<a href="https://agentmods.dev/skills/dragoon0x/taste-skills/field-notes"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/field-notes/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 field-notes

Your own site · 80×15
<a href="https://agentmods.dev/skills/dragoon0x/taste-skills/field-notes"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/field-notes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 343 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 $0.00042 $0.00343
Opus 5 $0.00021 $0.00171
Sonnet 5 $0.00008 $0.00069
Haiku 4.5 $0.00004 $0.00034

Measured 9d ago against content hash 2ab46c7e6274, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

field-notes 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 9d 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/evaluation/field-notes/SKILL.md · 37 lines

What it actually says

Field Notes

The format for making taste observations legible.

How to use

  • /field-notes Write a structured taste breakdown of a product in this conversation.
  • /field-notes <product> Analyze the specified product using the field notes format.

Constraints

Field Note Structure

  1. Product name, URL, date, category
  2. What it's trying to be (2-3 sentences. Not what it does. What experience it's trying to create.)
  3. Three things that work (specific decisions with principles behind them)
  4. One thing that doesn't (specific decision with reasoning and impact)
  5. The taste principle (one sentence: "This product demonstrates that...")
  6. Tags (principle-based tags for the reference library)

Writing Rules

  • MUST be specific. Reference actual elements, sizes, and interactions.
  • MUST connect every observation to a principle.
  • MUST include at least one thing that doesn't work. No product is perfect.
  • SHOULD be under 500 words. Concise analysis is harder and more useful than exhaustive analysis.
  • NEVER write a field note about a product you haven't actually used.

Anti-Patterns

  • Writing only about famous products everyone has already analyzed
  • Describing what the product does instead of how it feels to use
  • Listing features instead of evaluating decisions
  • Being uniformly positive (honest analysis includes what falls short)
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. 9d ago First seen · 37 lines · 42 tokens per session scan A 2ab46c7e6274

Subscribe to this mod's changes

field-notes is a skill published in the GitHub repository Dragoon0x/taste-skills (4 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 343 once invoked, about $0.0002 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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