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/mizukaizen/hive-doctrine-mcpWrote 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/mizukaizen/hive-doctrine-mcp/scan)<a href="https://agentmods.dev/commands/mizukaizen/hive-doctrine-mcp/scan"><img src="https://agentmods.dev/badge/commands/mizukaizen/hive-doctrine-mcp/scan/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/mizukaizen/hive-doctrine-mcp/scan"><img src="https://agentmods.dev/badge/commands/mizukaizen/hive-doctrine-mcp/scan.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 | $0.00641 |
| Opus 5 | $0.00000 | $0.00320 |
| Sonnet 5 | $0.00000 | $0.00128 |
| Haiku 4.5 | $0.00000 | $0.00064 |
Grade A, and why
scan 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 9d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/scan
Run a comprehensive security scan across dependencies, code, and configuration.
Usage
/scan [--scope "full|deps|code|config|secrets"] [--severity "critical,high,medium,low"] [--fix]
Behaviour
1. Dependency Audit
Scan package manifests for known vulnerabilities:
- Node.js:
npm auditor parsepackage-lock.jsonagainst advisory databases - Python: Check
requirements.txtorPipfile.lockagainst safety/pip-audit databases - Rust: Parse
Cargo.lockagainst RustSec advisory database - Go: Parse
go.sumagainst Go vulnerability database
For each vulnerable dependency, report:
- Package name and installed version
- CVE identifier and CVSS score
- Fixed version (if available)
- Whether it is a direct or transitive dependency
2. Static Analysis (SAST)
Scan source code for security anti-patterns:
- SQL injection: string concatenation in queries, unsanitised user input in SQL
- XSS: unescaped user input in HTML output, innerHTML usage
- Command injection: user input in shell commands, exec/eval usage
- Path traversal: user input in file paths without sanitisation
- Insecure crypto: MD5/SHA1 for security purposes, ECB mode, hardcoded IVs
- Insecure randomness: Math.random() for security-sensitive operations
3. Secrets Detection
Scan all files for leaked credentials:
- API keys (common provider patterns:
sk-,AKIA,ghp_, etc.) - Private keys (RSA/EC/Ed25519 PEM headers)
- Passwords in configuration files
- Connection strings with embedded credentials
- JWT tokens
- AWS/GCP/Azure credential patterns
4. Configuration Audit
Check for misconfigurations:
- Docker: running as root, exposed ports, no health checks, secrets in build args
- CI/CD: secrets in plain text, untrusted actions, missing branch protections
- Cloud: public S3 buckets, overly permissive IAM, missing encryption
- Application: debug mode in production, CORS wildcards, missing security headers
5. Report
Generate a scan report in security/scans/[date]/report.md:
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.
- 9d ago First seen · 83 lines · 0 tokens per session scan A 18a7d5cc686d
scan is a command published in the GitHub repository mizukaizen/hive-doctrine-mcp (0 stars, last pushed 2mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 641 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.
Other commands, from other repositories
mega-approve
Approve the mega-plan and start feature execution. Creates worktrees and generates PRDs for each feature. Usage: /plan-cascade:mega-approve [--flow ] [--tdd ] [--confirm] [--no-confirm] [--spec ] [--first-principles] [--max-questions N] [--auto-prd] [--agent ] [--prd-agent ] [--impl-agent ].
auto
AI auto strategy executor. Analyzes task and automatically selects and executes the best strategy: direct execution, hybrid-auto PRD generation, hybrid-worktree isolated development, or mega-plan multi-feature orchestration.
design-generate
Generate a technical design document. Auto-detects level: project-level from mega-plan.json, or feature-level from prd.json. Provides architectural context for story execution.
design-review
Review and interactively edit the current designdoc.json. Displays the design document in a readable format and allows modifications to components, patterns, decisions, and story mappings.
worktree
Start a new task in an isolated Git worktree for parallel multi-task development. Creates a task branch, worktree directory with planning files, and leaves the main directory untouched. Usage: /plan-cascade:worktree [task-name] [target-branch]. Example: /plan-cascade:worktree feature-login main.
design-import
Import an external design document (Markdown, JSON, or HTML from Confluence/Notion) and convert it to designdoc.json format for Plan Cascade integration.