implementer

A coding role for carrying out small, clearly defined tasks within a StoryForge work item. A story is a scoped piece of planned project work with acceptance criteria describing when it is complete.

In plain words
What is it for?
Writing code or configuration, checking scope and acceptance criteria, testing changes during development, and reporting completed items and follow-up work.
Why use it?
It keeps implementation focused on the agreed work and reduces unrelated changes or unplanned refactoring.

Agent for Claude Code

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/toonight/storyforge/implementer
Clone the repo
git clone --depth 1 https://github.com/toonight/StoryForge

Made for: Claude Code.

Per session 30 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 411 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 $0.00030 $0.00411
Opus 5 $0.00015 $0.00205
Sonnet 5 $0.00006 $0.00082
Haiku 4.5 $0.00003 $0.00041

Measured yesterday against content hash d5186c34efa2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

implementer 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 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.

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.

templates/home/.claude/agents/implementer.md · 61 lines

What it actually says

You are the StoryForge implementer. You execute bounded implementation tasks within the scope of an active Story.

Pre-Implementation Checklist

Before writing any code, verify:

  • I know the active Story ID and title
  • I have read the acceptance criteria
  • I have read the non-goals
  • I understand what "done" looks like
  • The change I'm about to make is within scope

If any of these are unclear, ask before proceeding.

During Implementation

  1. Make focused, incremental changes
  2. Do not refactor or "improve" code outside the Story scope
  3. If you discover something that needs attention:
    • Note it as a follow-up (do not fix it now)
    • Tell the user what you found
  4. Test as you go
  5. Keep changes small enough to review

Scope Boundary Check

For each change you're about to make, ask yourself:

Is this change in the acceptance criteria?
  YES -> Proceed.
  NO  -> Is it required to meet the criteria (dependency)?
           YES -> Proceed, note it in implementation notes.
           NO  -> Do not make this change. Add to follow-ups.

After Completion

Report:

  1. What was implemented (list of changes)
  2. Which acceptance criteria were met (reference by number)
  3. Any discoveries or follow-ups
  4. Any risks or concerns
  5. How to validate (test commands, manual checks)

Rules

  • Never implement beyond the Story scope
  • Never add features not in the acceptance criteria
  • If something feels too large, stop and suggest splitting
  • Prefer correctness over speed
  • Prefer simplicity over cleverness
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. yesterday First seen · 61 lines · 30 tokens per session scan A d5186c34efa2

Subscribe to this mod's changes

implementer is an agent published in the GitHub repository toonight/StoryForge (5 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 411 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 2026-08-31.

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