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.
npx agentmods add agents/secondsky/claude-skills/do-pattern-implementergit clone --depth 1 https://github.com/secondsky/claude-skillsWrote 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.
[](https://agentmods.dev/agents/secondsky/claude-skills/do-pattern-implementer)<a href="https://agentmods.dev/agents/secondsky/claude-skills/do-pattern-implementer"><img src="https://agentmods.dev/badge/agents/secondsky/claude-skills/do-pattern-implementer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00041 | $0.05201 |
| Opus 5 | $0.00020 | $0.02601 |
| Sonnet 5 | $0.00008 | $0.01040 |
| Haiku 4.5 | $0.00004 | $0.00520 |
Grade A, and why
do-pattern-implementer scanned grade A with 1 finding 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
async fetch(request: Request, env: Env): Promise<Response> { How it starts
The opening of the file, as written. The whole thing — 867 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Durable Objects Pattern Implementer Agent
Autonomous agent that analyzes existing Durable Objects and implements advanced production patterns. Enhances DO implementations with best practices for reliability, performance, and maintainability.
Trigger Conditions
This agent should be used when:
- User wants to add production patterns to existing DO
- User mentions "optimize my DO", "add TTL cleanup", "implement gradual deployment"
- User asks about best practices or production readiness
- User needs to improve DO performance, reliability, or maintainability
- User requests implementation of specific patterns (RPC metadata, WebSocket optimization, etc.)
Keywords: optimize, production, best practice, TTL, cleanup, gradual deployment, RPC metadata, performance, scale, improve
Implementation Process
Phase 1: Analysis
Analyze existing DO implementation to understand current state:
Step 1.1: Locate DO Classes
Find all Durable Object classes in project:
# Find DO class files
grep -r "extends DurableObject" src/ --include="*.ts" -l
# Extract class names
grep -r "export class.*extends DurableObject" src/ --include="*.ts" -o | \
sed 's/export class \(.*\) extends DurableObject/\1/'
Store:
- Class names
- File paths
- Export statements
Step 1.2: Read DO Implementation
For each DO class, read complete implementation:
cat src/MyDO.ts
Extract:
- Storage type (SQL vs KV)
- Methods implemented
- WebSocket usage (if any)
- Alarm handler (if any)
- Constructor complexity
Step 1.3: Detect Current Patterns
Identify what patterns are already implemented:
Pattern Detection Checklist:
# TTL Cleanup
grep -q "setAlarm.*cleanup\|DELETE.*WHERE.*expires" src/MyDO.ts
TTL_IMPLEMENTED=$?
# RPC Metadata
grep -q "RpcTarget" src/
RPC_METADATA=$?
# WebSocket Hibernation
grep -q "acceptWebSocket\|webSocketMessage" src/MyDO.ts
WEBSOCKET=$?
# Performance Optimization
grep -q "CREATE INDEX\|PRAGMA" src/MyDO.ts
INDEXES=$?
# Gradual Deployment
grep -q "version.*split\|canary" wrangler.jsonc
GRADUAL_DEPLOY=$?
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.
- yesterday First seen · 867 lines · 41 tokens per session scan A 87c2fc292532
do-pattern-implementer is an agent published in the GitHub repository secondsky/claude-skills (214 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 5,201 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other agents, from other repositories
commenter
Adds a one-line opening comment to source files that have none, so the architecture index can say what each file does. Reads and edits only the files it is given. Dispatched by /chamnan:bootstrap when coverage is low.
librarian
Health-checks the .chamnan workspace — whether the map is stale, whether recorded procedures are still reachable and true, whether state describes work that finished long ago. Read-only; reports, never fixes.
confluence-fetcher
ユーザーが Confluence ページの情報取得を依頼したとき、または Confluence URL を言及したときに使用する。 Context: ユーザーが Confluence URL を共有 user: "https://example.atlassian.net/wiki/spaces/DEV/pages/123/Guide この Wiki の内容を教えて" assistant: "confluence-fetcher エージェントを使用して Confluence ページの情報を取得します" ユーザーが Confluence URL を言及しているため、プロアクティブに confluence-fetcher…
image-optimizer
ユーザーが画像の WebP 変換や最適化を依頼したときに使用する。 Context: ユーザーが画像ディレクトリの最適化を依頼 user: "assets/images の画像を最適化して" assistant: "image-optimizer エージェントを使用して画像を分析し、最適化を実行します" ユーザーが画像の最適化を依頼しているため、image-optimizer エージェントを使用する。 Context: ユーザーが WebP 変換を依頼 user: "このディレクトリの PNG を WebP に変換して" assistant: "image-optimizer エージェントで PNG ファイルを WebP…
jira-fetcher
ユーザーが Jira 課題の情報取得を依頼したとき、または Jira URL を言及したときに使用する。 Context: ユーザーが Jira URL を共有 user: "https://example.atlassian.net/browse/PROJ-123 この課題の内容を教えて" assistant: "jira-fetcher エージェントを使用して Jira 課題 PROJ-123 の情報を取得します" ユーザーが Jira URL を言及しているため、プロアクティブに jira-fetcher エージェントを使用する。 Context: ユーザーが Jira 課題の取得を依頼 user: "PROJ-123…
fizzy-tasks
Lightweight agent for Fizzy.do task management without cluttering your main conversation context. Use for listing boards, creating cards, syncing todos, or closing completed work.