taste-review

taste-review is a skill for Claude Code, Codex from humanerd-drew/opencode-drewgent. It costs 34 tokens per session (1,306 once invoked), scanned A, original, MIT.

A review process for studying a selected tool and recording the design decisions worth applying elsewhere. It researches the tool's documentation, architecture, user experience, and distinctive choices.

In plain words
What is it for?
Use it to select one item for deeper review, research its documentation, identify useful decisions, and record the findings in a knowledge vault.
Why use it?
It turns a list of interesting tools into concrete lessons instead of leaving them as unexamined links or notes.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions OpenCode.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is cp keep/xxxx.json ../../evaluated/YYYY-MM-DD-taste-{name}.json.

Good fit Use it to select one item for deeper review, research its documentation, identify useful decisions, and record the findings in a knowledge vault.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/humanerd-drew/opencode-drewgent
agentmods
npx agentmods add skills/humanerd-drew/opencode-drewgent/taste-review

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 taste-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/taste-review.svg)](https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/taste-review)
Your own site
<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/taste-review"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/taste-review.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,306 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 $0.00034 $0.01306
Opus 5 $0.00017 $0.00653
Sonnet 5 $0.00007 $0.00261
Haiku 4.5 $0.00003 $0.00131

Measured 4d ago against content hash 7b61c861fb3a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

taste-review 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.

skills/taste-review/SKILL.md · 149 lines

How it starts

The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Taste Review Skill

Trend Harvester가 수집+분석한 keep 리스트에서 1개를 골라 심층 분석하고, 그 툴에서 배울 수 있는 taste 결정을 추출하여 vault에 기록한다.

Execution Model — Kanban Delegation

Taste Review는 더 이상 직접 cron job에서 실행되지 않는다. 다음 플로우로 동작:

cron: taste-review-trigger (fast LLM, 화/금 10:00)
  → kanban_create(title="taste-review: YYYY-MM-DD", assignee="default")
    → kanban worker (본 분석 실행)
  • Trigger cron (taste-review-trigger, 66d907f7bce4): 빠른 모델(opencode-go/deepseek-v4-flash)로 keep 리스트 확인 → 새 항목 있으면 kanban task 생성 → 종료 (수초)
  • Kanban worker: 실제 분석 실행 (web_search + file write + LLM reasoning) — cron idle timeout(600s)과 무관

Phase 1 — Pick & Research

항목 선택

  1. analyzed/keep/ 디렉토리에서 아직 evaluated/에 없는 항목 1개 선택
  2. 이미 applied/ 또는 evaluated/에 있는 항목은 스킵

웹 리서치

  1. web_search 또는 직접 URL로 해당 툴의 README와 문서 탐색
  2. 다음에 집중:
    • 아키텍처 결정: 왜 이렇게 만들었을까? (언어, 패턴, 구조)
    • 사용자 경험 결정: 어떤 trade-off를 했을까?
    • 독특한 접근법: 다른 툴과 다른 점은?

Phase 2 — Analyze & Write

분석 프레임워크

다섯 가지 질문에 답변:

  1. One-Liner: 이 툴을 한 문장으로 설명하면?
  2. 훔칠 Taste 결정 (1-3개): 이 툴의 제작자가 내린 결정 중, {{AGENT_NAME}}에 적용할 가치가 있는 것은?
  3. 아키텍처 인사이트: 구조적으로 배울 점은?
  4. {{AGENT_NAME}} 적용 가능성: 이 아이디어를 {{AGENT_NAME}}에 적용할 수 있는가? 어떻게?
  5. Leverage Score (1-5): 이 인사이트가 {{AGENT_NAME}}에 미칠 영향은?

Vault 저장

Path: P4-cortex/taste-reviews/YYYY-MM-DD-tool-slug.md

Frontmatter:

---
title: "Taste Review: Tool Name"
type: taste-review
tags: [taste-review, YYYY-MM]
created: YYYY-MM-DD
links:
  - "[[trend-harvester]]"
  - "[[@memory/growth/trend-harvester/analyzed/keep/xxxx.json]]"
  - "[[@identity/brain/rules]]"
  session: "YYYY-MM-DD taste-review"
  trigger: "scheduled taste review"
---

Body:

# Taste Review: Tool Name

분석일: YYYY-MM-DD | 링크: [GitHub](url)

## One-Liner
...

## 훔칠 Taste 결정
### 1. [결정 제목]
- **무슨 결정인가:** ...
- **왜 taste가 필요한 결정인가:** ...
- **{{AGENT_NAME}}에 적용:** ...

### 2. ...

## 아키텍처 인사이트
...

## {{AGENT_NAME}} 적용 가능성
[Yes/No + 구체적 방법]

## Leverage Score: N/5

Read the full file on GitHub · 149 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 · 149 lines · 0 tokens per session scan A 7b61c861fb3a

Subscribe to this mod's changes

taste-review is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (2 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 1,306 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 2026-09-03.

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