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 commands/coralogix/canopy/explain-architecturegit clone --depth 1 https://github.com/coralogix/canopyWrote 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/coralogix/canopy/explain-architecture)<a href="https://agentmods.dev/commands/coralogix/canopy/explain-architecture"><img src="https://agentmods.dev/badge/commands/coralogix/canopy/explain-architecture.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 | $0.00000 | $0.00354 |
| Opus 5 | $0.00000 | $0.00177 |
| Sonnet 5 | $0.00000 | $0.00071 |
| Haiku 4.5 | $0.00000 | $0.00035 |
Grade A, and why
explain-architecture 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 5d 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.
What it actually says
/explain-architecture
Give a 5-minute architectural tour of the codebase in the current workspace directory.
Steps
- Identify the project type by reading top-level files:
package.json,pyproject.toml,Cargo.toml,go.mod,README.md, etc. - List the top-level directories and their apparent purpose.
- Find the entry point(s):
main.py,index.ts,main.go,src/main.rs,app.py,server.js, etc. - Identify the 3-5 most important modules or packages by looking at what the entry point imports and what has the most cross-references.
- Describe the data flow for the primary use case: how does a request or input enter the system, what transforms it, and where does it exit?
- Note any non-obvious architectural decisions: why is it structured this way? What constraints explain the design?
Output Format
## Project Type
[language, framework, build tool]
## Entry Points
[list with file paths]
## Key Modules
[module name] — [file path] — [what it does]
...
## Primary Data Flow
1. [step] → [file:line]
2. [step] → [file:line]
...
## Notable Design Decisions
- [decision]: [rationale inferred from code/comments]
Rules
- Read at least 5 files before answering — don't guess structure from top-level names alone
- Always cite file paths
- Keep each section to 3-5 lines max — this is an overview, not a deep dive
- If the codebase is unfamiliar, say what you're uncertain about
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.
- 5d ago First seen · 42 lines · 0 tokens per session scan A ded70bd37c0b
explain-architecture is a command published in the GitHub repository coralogix/canopy (89 stars, last pushed 4mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 354 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.