icdev
The System That Builds Systems. AI-powered SDLC with multi-framework compliance automation (NIST 800-53, FedRAMP, CMMC, STIG), 16 AI agents, 13 design canvases, FORGE framework, ANVIL build workflow, and ATO-ready artifact generation.
Install / Use
npx skills add icdev-ai/icdevInstalls into whichever agent you are using.
Amazon Q Rules
Amazon Q Developer rules
Quality Score
Category
AutomationSupported Platforms
Our assessment of icdev
icdev scores 56/100 on our quality scale, 1907th of 2,037 Automation skills we index.
Its Amazon Q Rules is 1.9 KB long, well organised into 8 sections with 1 code example: moderately detailed.
It has no GitHub stars yet, so there is no community track record; judge it on its content.
Maintenance, license and trust
- We could not determine when the repository was last updated.
- Our last check on 2026-09-27 found the source still online.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 68/100, with 3 cautions from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
icdev compared with similar skills
All 4 of these similar skills score higher than icdev; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| icdev (this skill)by icdev-ai | 56 | 0 | — | Amazon Q Rules |
| Agent-Reachby Panniantong | 100 | 86.0k | 13d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.4k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 84.3k | 1d ago | MCP Server |
| designby nextlevelbuilder | 100 | 130.2k | 7d ago | SKILL.md |
Frequently asked questions
- How do I install icdev?
- Run
npx skills add icdev-ai/icdev. The install tabs above show the steps for each supported agent. - Which AI agents does icdev work with?
- It is written for Amazon Q, as a Amazon Q Rules file. Other agents that read the same format can often use it too.
- Is icdev safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It declares no license and scores 68/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is icdev still maintained?
- We could not determine when the repository was last updated.
Skill content
View source on GitHubICDEV™ Project Rules — ICDEV™ Project
Project
| Field | Value | |-------|-------| | Type | webapp | | Language | python | | Impact Level | IL4 | | Classification | CUI | | Cloud | aws_govcloud |
Architecture
FORGE framework: deterministic Python tools in tools/ with --json output. Goals in goals/, config in args/.
AWS GovCloud
This project targets aws_govcloud. All LLM inference via Amazon Bedrock. Secrets via AWS Secrets Manager.
Coding Rules
- CUI marking required:
# CUI // SP-CTI - snake_case, 100-char lines, pytest >= 80%
Commands
python tools/project/session_context_builder.py --format markdown
pytest tests/ -v
python tools/security/sast_runner.py --project-dir . --json
python tools/compliance/ssp_generator.py --project-id "" --json
MCP
2 servers. Config: .amazonq/mcp.json — run python tools/dx/mcp_config_generator.py --platform amazon_q --write.
Generated by ICDEV™ Companion
Karpathy Principles — Pre-Design Engineering Gate
Before writing code, apply these 5 heuristics from hardprompts/karpathy_principles.md:
- State assumptions — Name the constraints, inputs, invariants you're relying on. Unstated assumptions are where bugs hide.
- Enumerate interpretations — For any ambiguous requirement, list the 2–4 ways it could be read before picking one. Surface them to the user if the choice is load-bearing.
- Prefer simpler — Three similar lines beats one clever abstraction. Don't design for hypothetical future requirements. YAGNI.
- Bound your edit scope — Only touch what the task requires. No drive-by refactors, no surrounding cleanup, no speculative error handling.
- Success criteria — State how you'll know the change is done before writing it. If you can't write the test / acceptance check, the spec is incomplete.
Applies to: build, bug fix, refactor, TDD, and code review workflows.
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Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.