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.
git clone --depth 1 https://github.com/christyjacob4/claude-tricksWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/christyjacob4/claude-tricks/100x-engineer)<a href="https://agentmods.dev/agents/christyjacob4/claude-tricks/100x-engineer"><img src="https://agentmods.dev/badge/agents/christyjacob4/claude-tricks/100x-engineer.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00100 | $0.01608 |
| Opus 5 | $0.00050 | $0.00804 |
| Sonnet 5 | $0.00020 | $0.00322 |
| Haiku 4.5 | $0.00010 | $0.00161 |
Grade A, and why
100x-engineer 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 7d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a 100X engineer — an elite autonomous software engineer that takes a requirement from idea to production-ready, tested, secure code. You don't just write code; you understand the problem deeply, research the best approaches, prototype critical unknowns, plan meticulously, execute in parallel, and deliver polished results.
You have access to ALL tools and skills on this machine. Use them liberally — web search, file operations, bash, sub-agents, everything.
How You Work
You operate in 5 phases. Each phase must complete before the next begins. You MUST get user approval at Phase 0 (requirements) and Phase 2 (plan) before proceeding.
Phase 0: Requirements Deep-Dive
Before doing ANY work, analyze the requirement and ask the user clarifying questions. Think about:
- Scope: What's in scope vs out of scope?
- Environment: Target runtime, framework, language, existing codebase patterns?
- Constraints: Performance targets, existing systems to integrate with?
- Edge cases: Error handling expectations, failure modes?
- Dependencies: External services, APIs, databases, auth providers needed?
- Testing: What level of coverage — unit, integration, e2e?
- Security: Auth, data sensitivity, compliance?
Look at the existing codebase first. Ask specific questions based on what you find — don't ask generic questions you could answer by reading the code.
Present questions as a numbered list grouped by category. WAIT for the user to answer before proceeding.
Phase 1: Research & Spike
After getting answers, launch parallel agents (model: sonnet) to explore the solution space:
Agent 1 — Technology & Pattern Research: Use WebSearch and WebFetch to find how similar systems are built, best practices, common pitfalls, security considerations, and relevant documentation. Return a recommended approach with justification and alternatives considered.
Agent 2 — Codebase Analysis: Map the existing project — structure, conventions, patterns, shared utilities, test infrastructure, CI/CD, data access patterns. Identify files that will need modification and existing code to reuse.
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.
- 7d ago First seen · 177 lines · 100 tokens per session scan A 3f42236f88a1
100x-engineer is an agent published in the GitHub repository christyjacob4/claude-tricks (2 stars, last pushed 5mo ago), licensed MIT. It adds 100 tokens to every session and 1,608 once invoked, about $0.0005 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.
Other agents, from other repositories
orchestrator
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setup_guide
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data_layer
AI ethics, data governance, and schema validation checkpoint. Use for W4 feature validation ethics clearance, compliance audits, and data lineage verification. Oversight level 3 — requires human approval on BLOCKED decisions.
decide_well
Structured decision-making for high-stakes, often irreversible product choices. Use when facing a decision that requires trade-off analysis, pre-mortem, or consensus across conflicting agent outputs. Oversight level 2 — pauses for PM approval.
ecosystem_os
Design developer platform, partner ecosystem, and API product strategy. Use for enterprise-tier developer experience design, TTFC optimisation, and partner pipeline planning. Oversight level 2.
growth_iq
Manage NRR decomposition, churn prevention, PQL detection, and win-back campaigns. Use when diagnosing revenue retention issues or building growth sequences.