dev

dev is an agent for coding agents from kangraemin/ai-bouncer. It costs 67 tokens per session (622 once invoked), scanned A, original, no licence file.

A development agent that implements a step assigned by a lead developer. It checks that the build succeeds and reports the result in a required format.

In plain words
What is it for?
Use it to carry out defined development steps, verify builds, and send structured status reports.
Why use it?
It delegates implementation and build verification while keeping progress reports consistent.

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/kangraemin/ai-bouncer/dev
Clone the repo
git clone --depth 1 https://github.com/kangraemin/ai-bouncer

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 dev

README.md
[![agentmods](https://agentmods.dev/badge/agents/kangraemin/ai-bouncer/dev.svg)](https://agentmods.dev/agents/kangraemin/ai-bouncer/dev)
Your own site
<a href="https://agentmods.dev/agents/kangraemin/ai-bouncer/dev"><img src="https://agentmods.dev/badge/agents/kangraemin/ai-bouncer/dev.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 622 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 $0.00067 $0.00622
Opus 5 $0.00034 $0.00311
Sonnet 5 $0.00013 $0.00124
Haiku 4.5 $0.00007 $0.00062

Measured 4d ago against content hash 5e5776588321, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

dev 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.

agents/dev.md · 71 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

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 · 71 lines · 67 tokens per session scan A 5e5776588321

Subscribe to this mod's changes

dev is an agent published in the GitHub repository kangraemin/ai-bouncer (3 stars, last pushed 2mo ago), with no licence file. It adds 67 tokens to every session and 622 once invoked, about $0.0003 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.

Related

Other agents, from other repositories

check

Code quality auditor for the Trellis channel runtime. Reviews uncommitted diffs against task artifacts and specs, self-fixes issues, and reports verification results.

mindfold-ai/Trellis · 34 tokens

vc-innovate-agent

INNOVATE MODE - Brainstorming and exploring implementation approaches. Discusses possibilities without making decisions. Use after research is complete.

withkynam/vibecode-pro-max-kit · 32 tokens

vc-ui-ux-designer

Use this agent when the user needs UI/UX execution support including interface implementation, design-system polish, responsive layouts, animations, accessibility review, or design documentation. Examples:\n\n \nContext: User wants to implement a new landing page from an approved direction\nuser: "I need a modern…

withkynam/vibecode-pro-max-kit · 428 tokens

adversarial-planner

Independent adversary for an implementation PLAN, before any code is written. Attacks the written plan's scope, non-goals, and decisions against the committed constraints it must honor, and surfaces only grounded objections for the human to decide. Never rewrites the plan and never sees the author's reasoning …

jakubsuplicki/codument · 82 tokens

integration-verifier

Verifies that the tasks of a completed build actually wire together. Dispatched once at /execute Step 4 for multi-task specs. Read-only -- cannot modify the codebase. Checks cross-task wiring + global acceptance, not per-task acceptance.

dwarvesf/dwarves-kit · 53 tokens

data-etl-worker

Implements a data pipeline/transform task, extract/transform/load, parsing, dedup, normalization. Write-capable; prefers DuckDB SQL for the transform per the house stack. Dispatched by /kit:execute step 2b-0 as the data-etl domain implementer.

dwarvesf/dwarves-kit · 64 tokens