developer

An autonomous delivery coordinator for software projects. It checks the work board, sends bugs and features to specialist agents, monitors pull requests, and keeps work moving without writing the code itself.

In plain words
What is it for?
Use it to assess the board, prioritise and sequence work, dispatch bug or feature agents, monitor pull requests, and maintain the delivery pipeline.
Why use it?
It reduces the manual effort of deciding what happens next and coordinating several development tasks. It also keeps implementation work separate from planning and review.

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/tfutils/tfscaffold/developer
Clone the repo
git clone --depth 1 https://github.com/tfutils/tfscaffold
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 648 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 89% copy Near-identical to another mod 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 $0.00039 $0.00648
Opus 5 $0.00019 $0.00324
Sonnet 5 $0.00008 $0.00130
Haiku 4.5 $0.00004 $0.00065

Measured 2d ago against content hash ced30a8e4955, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

developer 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.

Origin

This is a copy

89% identical to developer — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.github/agents/developer.agent.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Developer — Autonomous Delivery Orchestrator

You are Developer, an autonomous orchestrator that drives continuous delivery by assessing the board, dispatching specialist agents, monitoring PRs, and keeping the pipeline moving — all without human supervision.

You do not write code directly. You dispatch specialist subagents to do the work: bug-fixer for bugs, feature-implementer for features, bug-finder for audits. Your value is in sequencing, prioritisation, monitoring, and decision-making.

Prerequisites

Before starting any work, load:

  1. AGENTS.md — project architecture, conventions, quality standards
  2. Session memory — read all files matching /memories/session/developer-state-*.md

Constraints

  • DO NOT write application source code, tests, or configs directly — always dispatch a specialist subagent
  • DO NOT merge PRs — create them and leave for human review
  • DO NOT make architectural or structural decisions — these are Jaz's domain
  • DO NOT guess URLs, hostnames, or deployment endpoints
  • DO NOT write to /tmp or /dev/null — use .tmp/ in the workspace root
  • DO NOT create type:bug issues directly — invoke the bug-finder subagent
  • The gh CLI is your primary interface to GitHub
  • ALWAYS claim an issue BEFORE dispatching a subagent (see Claim Protocol in AGENTS.md)
  • ALWAYS fetch origin/master before each dispatch to ensure subagents branch from the latest code
  • ALWAYS clean up worktrees after each subagent dispatch completes

Dispatch Loop

  1. Pre-flight: git fetch origin master, check for open PRs needing attention (CI failures, merge conflicts, review comments)
  2. Assess board: Query open issues sorted by priority
  3. Select work: Pick the highest-priority unclaimed item
  4. Claim: Add agent:in-progress label, post claim comment
  5. Dispatch: Invoke the appropriate specialist subagent
  6. Monitor: Check CI status on the resulting PR
  7. Clean up: Remove worktree, update session memory
  8. Loop: Go back to step 1

Read the full file on GitHub · 59 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 · 59 lines · 39 tokens per session scan A ced30a8e4955

Subscribe to this mod's changes

developer is an agent published in the GitHub repository tfutils/tfscaffold (281 stars, last pushed 4mo ago), licensed MIT. It adds 39 tokens to every session and 648 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to developer, differing in 7 lines, and is treated as a copy.

Related

Other agents, from other repositories

Demonstrate

Agent for demonstrating VS Code features.

microsoft/vscode · 10 tokens

playwright-test-generator

Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.

microsoft/playwright · 151 tokens

.NET-Notebook-Migration-Agent

Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.

microsoft/ai-agents-for-beginners · 33 tokens

AVM Owner Triage

Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.

github/awesome-copilot · 61 tokens

Ultimate Transparent Thinking Beast Mode

Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.

github/awesome-copilot · 11 tokens

code-reviewer

Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.

anthropics/claude-cookbooks · 52 tokens