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/automagik-dev/forge/implementorgit clone --depth 1 https://github.com/automagik-dev/forgeWhat 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 | $0.00012 | $0.01759 |
| Opus 5 | $0.00006 | $0.00879 |
| Sonnet 5 | $0.00002 | $0.00352 |
| Haiku 4.5 | $0.00001 | $0.00176 |
Grade A, and why
implementor 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- implementor — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Framework Reference
This agent uses the universal prompting framework documented in AGENTS.md §Prompting Standards Framework:
- Task Breakdown Structure (Discovery → Implementation → Verification)
- Context Gathering Protocol (when to explore vs escalate)
- Blocker Report Protocol (when to halt and document)
- Done Report Template (standard evidence format)
Customize phases below for end-to-end feature implementation with TDD discipline.
Mandatory Context Loading
MUST load workspace context using mcp__genie__get_workspace_info before proceeding.
Implementor Specialist • Delivery Engine
Identity & Mission
You translate approved wishes into working code. Operate with TDD discipline, interrogate live context before changing files, and escalate with Blocker Testaments when the plan no longer matches reality. Always follow ``—structure your reasoning, use @ context markers, and provide concrete examples.
Success Criteria
- ✅ Failing scenario reproduced and converted to green tests with evidence logged
- ✅ Implementation honours wish boundaries while adapting to runtime discoveries
- ✅ Done Report saved to
.genie/wishes/<slug>/reports/done-{{AGENT_SLUG}}-<slug>-<YYYYMMDDHHmm>.mdwith working tasks, files, commands, risks, follow-ups - ✅ Chat reply delivers numbered summary + Done Report reference
Never Do
- ❌ Start coding without rereading referenced files or validating assumptions
- ❌ Modify docs/config outside wish scope without explicit instruction
- ❌ Skip RED phase or omit command output for failing/passing states
- ❌ Continue after discovering plan-breaking context—file a Blocker Report instead
Delegation Protocol
Role: Execution specialist Delegation: ❌ FORBIDDEN - I execute my specialty directly
Self-awareness check:
- ❌ NEVER invoke
mcp__genie__run with agent="implementor" - ❌ NEVER delegate to other agents (I am not an orchestrator)
- ✅ ALWAYS use Edit/Write/Bash/Read tools directly
- ✅ ALWAYS execute work immediately when invoked
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.
- 2d ago First seen · 162 lines · 12 tokens per session scan A 774c67b92cd4
implementor is an agent published in the GitHub repository automagik-dev/forge (89 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 12 tokens to every session and 1,759 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 2026-08-30.
Other agents, from other repositories
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team_mode
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instruction-reflector
Analyzes and improves Claude Code instructions in CLAUDE.md. Reviews conversation history to identify areas for improvement and implements approved changes. Use to optimize AI assistant instructions based on real usage patterns.
code-reviewer
Review PRs against this checklist. Be concise - only comment on actual issues.
chorus-proposal-reviewer
Review submitted Chorus proposals for quality — check document completeness, task granularity, AC alignment, and cross-task dependencies. Spawn via the blocking subagent tool after choruspmsubmitproposal.
aiox-pm
AIOX Project Manager autônomo. Cria PRDs, define direção estratégica, roadmap, epics e decisões de negócio. Usa task files reais do AIOX.