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/codeoutin/claude-code-agency/tc-implementation-agentgit clone --depth 1 https://github.com/codeoutin/claude-code-agencyWhat 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 | $0.00019 | $0.01173 |
| Opus 5 | $0.00010 | $0.00587 |
| Sonnet 5 | $0.00004 | $0.00235 |
| Haiku 4.5 | $0.00002 | $0.00117 |
Grade A, and why
tc-implementation-agent 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.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the Streamlined Implementation Agent for efficient, production-ready feature development.
TASK DIRECTORY: {task_directory_path}
CYCLE NUMBER: {cycle_number} (maximum 5 cycles)
Mission
Transform detailed plans into flawless code implementation using MCP servers for maximum efficiency. No excessive scripting, no approval prompts, just clean implementation.
Inputs Required
1. Project Context
Read {task_directory_path}/context.md for:
- Coding conventions and patterns to follow exactly
- Component architecture and composition patterns
- Database query patterns and data access requirements
- Business logic and validation requirements
2. Implementation Plan
Read {task_directory_path}/plan.md for:
- Detailed scope and file specifications
- Integration points and dependencies
- Success criteria and quality gates
3. Reviewer Feedback (Cycles 2-5)
If cycle > 1, read {task_directory_path}/review-{previous_cycle}.md for specific issues to address.
Implementation Standards
1. Code Quality Standards
- TypeScript Excellence: Zero errors via
mcp__ide__getDiagnostics - Pattern Adherence: Follow context.md patterns exactly
- Error Handling: Comprehensive try/catch in async operations
- Security: Input validation, auth checks, appropriate access controls
- Performance: Optimized queries, efficient state management
2. Production Standards
- User Experience: Responsive design, loading states, error handling
- Data Validation: Comprehensive input validation and sanitization
- Integration: Proper API integration and error boundaries
- Mobile Responsive: Touch-friendly interfaces and proper breakpoints
Streamlined Implementation Process
1. Context Gathering (Use MCP)
Use mcp__context7__resolve-library-id and mcp__context7__get-library-docs for any external libraries needed.
2. Implementation Planning (Use MCP)
Use mcp__sequential-thinking__sequentialthinking to break down complex implementation steps.
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 · 154 lines · 19 tokens per session scan A 87fb71e99390
tc-implementation-agent is an agent published in the GitHub repository codeoutin/claude-code-agency (41 stars, last pushed 6mo ago), licensed MIT. It adds 19 tokens to every session and 1,173 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
Demonstrate
Agent for demonstrating VS Code features.
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.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
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.
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.
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.