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/DauQuangThanh/hanoi-rainbowWrote 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/commands/dauquangthanh/hanoi-rainbow/assess-context)<a href="https://agentmods.dev/commands/dauquangthanh/hanoi-rainbow/assess-context"><img src="https://agentmods.dev/badge/commands/dauquangthanh/hanoi-rainbow/assess-context/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/commands/dauquangthanh/hanoi-rainbow/assess-context"><img src="https://agentmods.dev/badge/commands/dauquangthanh/hanoi-rainbow/assess-context.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 | $0.00017 | $0.02911 |
| Opus 5 | $0.00009 | $0.01456 |
| Sonnet 5 | $0.00003 | $0.00582 |
| Haiku 4.5 | $0.00002 | $0.00291 |
Grade A, and why
assess-context 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 10d 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 — 418 lines — stays where its author put it; the contents beside it link to each section on GitHub.
User Input
$ARGUMENTS
You MUST consider the user input before proceeding (if not empty).
Outline
IMPORTANT: Automatically generate a 'docs:' prefixed git commit message (e.g., 'docs: add codebase context assessment') and commit context-assessment.md upon completion.
-
Setup: Run
{SCRIPT}from repo root and parse JSON for CONTEXT_ASSESSMENT, DOCS_DIR, REPO_ROOT, HAS_GIT. -
Load context: Read
memory/ground-rules.md(if exists),docs/architecture.md(if exists),docs/standards.md(if exists). Load CONTEXT_ASSESSMENT template (already copied). Adhere to the principles for maximizing system clarity, structural simplicity, and long-term maintainability. -
Execute context assessment workflow: Follow the structure in CONTEXT_ASSESSMENT template to:
- Identify technology stack and frameworks
- Analyze project structure and organization
- Document architectural patterns and design decisions
- Extract coding conventions and standards
- Map key components and their relationships
- Identify data models and storage patterns
- Document API contracts and integration patterns
- Assess testing approach and coverage
- Review build and deployment processes
- Calculate technical health score
-
Update agent context: Run
{AGENT_SCRIPT}to update agent-specific context with assessment findings. -
Stop and report: Command ends after assessment completion. Report CONTEXT_ASSESSMENT path and technical health score.
Phases
Phase 0: Technology Stack Discovery
-
Identify core technologies:
- Programming languages and versions (package.json, requirements.txt, pom.xml, etc.)
- Frameworks and major libraries
- Runtime environment (Node.js, Python, Java, .NET, etc.)
- Database systems (PostgreSQL, MongoDB, Redis, etc.)
- Build tools (npm, pip, Maven, Gradle, etc.)
-
Document development environment:
- Required tools and versions
- Environment setup requirements
- Local development scripts
- Configuration management approach
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.
- 10d ago First seen · 418 lines · 17 tokens per session scan A 17d377ed3954
assess-context is a command published in the GitHub repository DauQuangThanh/hanoi-rainbow (16 stars, last pushed 7mo ago), licensed MIT. It adds 17 tokens to every session and 2,911 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
sddp-qc
Command description: Run quality control against the implemented feature. Argument hint: [optional: testing focus such as unit tests, security audit, requirements sync] Command category: feature-delivery Prerequisites: spec, plan, tasks, implementation:complete.
refactor-clean
You are a code refactoring expert specializing in clean code principles, SOLID design patterns, and modern software engineering best practices. Analyze and refactor the provided code to improve its quality, maintainability, and performance.
default-ai-review
Extract findings from the provided diff. Rank by severity. Produce a structured review. Emit one recommendation.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
validate-pr-description
Use when validating a PR title and description for conventional commit format, issue linking keywords, and template compliance before submission.
analyst
Use when performing local analyst review before pushing PR changes. Assesses code quality, impact analysis, and maintainability.