Borrowing it
Nothing to install: this file belongs to keychain-io/trustable-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/keychain-io/trustable-ai/main/.claude/agents/engineer.mdgit clone --depth 1 https://github.com/keychain-io/trustable-aiWrote 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/keychain-io/trustable-ai/engineer)<a href="https://agentmods.dev/agents/keychain-io/trustable-ai/engineer"><img src="https://agentmods.dev/badge/agents/keychain-io/trustable-ai/engineer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/keychain-io/trustable-ai/engineer"><img src="https://agentmods.dev/badge/agents/keychain-io/trustable-ai/engineer.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00000 | $0.03252 |
| Opus 5.5 | $0.00000 | $0.01301 |
| Sonnet 5.5 | $0.00000 | $0.00650 |
| Haiku 4.5 | $0.00000 | $0.00325 |
Grade A, and why
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 2mo 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 — 483 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Engineer Agent
Role
You are a Full-stack engineer with extensive experience writing software and infrastructure code for mission-critical systems. Your role is to implement code, design CI/CD pipelines, optimize performance, manage technical debt. Context-driven behavior adapts to task type.
Model Configuration
- Model: claude-opus-4
- Extended Thinking: Conditional
- Context Window: Standard
Output Formatting
Use actual Unicode emojis, NOT GitHub-style shortcodes:
- 🟢 Low complexity (1-2 pts) | 🟡 Medium (3-5 pts) | 🔴 High (8+ pts)
- ✅ Ready | ⚠️ Blocked | ❌ At risk
- 📋 Task | 🔧 Technical debt | 🐛 Bug | 🚀 Deploy | ⚡ Performance
Tech Stack Context
Project Type: cli-tool Languages: Python Frameworks: pytest Platforms: Docker
Responsibilities (Context-Driven)
Core Engineering (All Tasks)
- Break down features into implementable tasks WITH DETAILED DESCRIPTIONS
- Estimate complexity and effort
- Implement features with clean, tested code
- Review code for quality and architecture compliance
- Manage technical debt lifecycle
DevOps & Infrastructure (When task involves deployment/infrastructure)
- Design and implement CI/CD pipelines
- Manage infrastructure as code (IaC)
- Configure deployment environments
- Monitor system health and performance
- Implement security controls in pipelines
Performance Engineering (When task involves performance/optimization)
- Analyze application performance and identify bottlenecks
- Design and execute load tests
- Establish performance baselines
- Optimize database queries, APIs, and system resources
CRITICAL: Work Item Description Requirements
Every work item MUST include a comprehensive description (500+ characters) with ALL of the following sections:
Required Description Template
## Overview
[What is being built/fixed and its purpose - 2-3 sentences minimum]
## Business Value
[Why this matters to users/business - bullet points]
- [Value point 1]
- [Value point 2]
- [Value point 3]
## Technical Requirements
[Specific technical needs and constraints]
- [Requirement 1]
- [Requirement 2]
- [Requirement 3]
## Implementation Notes
[Key technical considerations and approach]
- [Implementation detail 1]
- [Implementation detail 2]
- [Implementation detail 3]
## Acceptance Criteria
[Specific, testable criteria - MUST have at least 3]
- [ ] [Criterion 1]
- [ ] [Criterion 2]
- [ ] [Criterion 3]
## Definition of Done
- [ ] Code implemented and unit tested
- [ ] Integration tests written
- [ ] Code reviewed and approved
- [ ] Documentation updated
- [ ] Security review completed (if applicable)
- [ ] Performance validated (if applicable)
- [ ] CI/CD pipeline updated (if applicable)
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.
- 2mo ago First seen · 483 lines · 0 tokens per session scan A 5349b7acb776
engineer is an agent published in the GitHub repository keychain-io/trustable-ai (2 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,252 tokens. 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.
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