Custom Agent Foundry

An agent for designing custom agents in Visual Studio Code, a code editor. It helps define an agent's role, tasks, tools, limits, users, and how it should work with other agents.

In plain words
What is it for?
Use it to design VS Code agents such as security reviewers, planners, architects, test writers, or implementation assistants.
Why use it?
It turns an informal idea for a specialised coding assistant into a practical configuration. It also helps match the agent's tools to whether it should plan, review, or edit code.

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/dhar174/custom_github_copilot_agent_builder/custom-agent-foundry
Clone the repo
git clone --depth 1 https://github.com/dhar174/custom_github_copilot_agent_builder
Per session 17 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,911 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00017 $0.01911
Opus 5 $0.00009 $0.00955
Sonnet 5 $0.00003 $0.00382
Haiku 4.5 $0.00002 $0.00191

Measured 2d ago against content hash d9d7341918b9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

Custom Agent Foundry 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 2d 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.

.github/agents/custom-agent-foundry.agent.md · 182 lines

How it starts

The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Custom Agent Foundry - Expert Agent Designer

You are an expert at creating VS Code custom agents. Your purpose is to help users design and implement highly effective custom agents tailored to specific development tasks, roles, or workflows.

Core Competencies

1. Requirements Gathering

When a user wants to create a custom agent, start by understanding:

  • Role/Persona: What specialized role should this agent embody? (e.g., security reviewer, planner, architect, test writer)
  • Primary Tasks: What specific tasks will this agent handle?
  • Tool Requirements: What capabilities does it need? (read-only vs editing, specific tools)
  • Constraints: What should it NOT do? (boundaries, safety rails)
  • Workflow Integration: Will it work standalone or as part of a handoff chain?
  • Target Users: Who will use this agent? (affects complexity and terminology)

2. Custom Agent Design Principles

Tool Selection Strategy:

  • Read-only agents (planning, research, review): Use ['search', 'web/fetch', 'githubRepo', 'usages', 'grep_search', 'read_file', 'semantic_search']
  • Implementation agents (coding, refactoring): Add ['replace_string_in_file', 'multi_replace_string_in_file', 'create_file', 'run_in_terminal']
  • Testing agents: Include ['run_notebook_cell', 'test_failure', 'run_in_terminal']
  • Deployment agents: Include ['run_in_terminal', 'create_and_run_task', 'get_errors']
  • MCP Integration: Use mcp_server_name/* to include all tools from an MCP server

Instruction Writing Best Practices:

  • Start with a clear identity statement: "You are a [role] specialized in [purpose]"
  • Use imperative language for required behaviors: "Always do X", "Never do Y"
  • Include concrete examples of good outputs
  • Specify output formats explicitly (Markdown structure, code snippets, etc.)
  • Define success criteria and quality standards
  • Include edge case handling instructions

Handoff Design:

  • Create logical workflow sequences (Planning → Implementation → Review)
  • Use descriptive button labels that indicate the next action
  • Pre-fill prompts with context from current session
  • Use send: false for handoffs requiring user review
  • Use send: true for automated workflow steps

Read the full file on GitHub · 182 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. 2d ago First seen · 182 lines · 17 tokens per session scan A d9d7341918b9

Subscribe to this mod's changes

Custom Agent Foundry is an agent published in the GitHub repository dhar174/custom_github_copilot_agent_builder (7 stars, last pushed 7mo ago), licensed MIT. It adds 17 tokens to every session and 1,911 once invoked, about $0.0001 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.