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/schedule)<a href="https://agentmods.dev/commands/mizukaizen/hive-doctrine-mcp/schedule"><img src="https://agentmods.dev/badge/commands/mizukaizen/hive-doctrine-mcp/schedule/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/schedule"><img src="https://agentmods.dev/badge/commands/mizukaizen/hive-doctrine-mcp/schedule.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 | $0.00562 |
| Opus 5 | $0.00000 | $0.00281 |
| Sonnet 5 | $0.00000 | $0.00112 |
| Haiku 4.5 | $0.00000 | $0.00056 |
Grade A, and why
schedule 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Command: /schedule
Create a social media schedule from recently published content. Extracts shareable quotes, key insights, and repurposed content for distribution across platforms.
Usage
/schedule [file-path or "latest"]
If "latest," use the most recently modified file in content/blog/.
Process
Step 1: Extract Content
Read the source blog post and identify:
- 5-8 standalone quotes or insights that work as social posts
- The core argument condensed into a thread (5-10 posts)
- 1 question that invites engagement
- 1 contrarian or surprising take from the content
Step 2: Generate Social Content
Thread (publish day 1):
Post 1: Hook — the most surprising or valuable insight from the post
Post 2-8: Key points, each standing alone
Post 9: Summary takeaway
Post 10: CTA — link to full post, invite replies
Standalone Posts (days 2-7):
- Each post contains one insight from the source content
- Varied format: quote, question, tip, stat, opinion
- Each includes a subtle reference to the full post (but works without it)
Newsletter Segment:
- 100-150 word summary suitable for inclusion in a weekly newsletter
- Links to the full post
Step 3: Create Schedule
# Social Schedule: [Post Title]
**Source:** [file path]
**Published:** [blog publish date]
## Day 1 — Thread
**Platform:** [Twitter/LinkedIn/Threads]
**Time:** [optimal posting time]
1. [Thread post 1]
2. [Thread post 2]
...
## Day 2 — Standalone Post
**Platform:** [Platform]
**Time:** [Time]
**Content:** [Post text]
## Day 3 — Question Post
**Platform:** [Platform]
**Time:** [Time]
**Content:** [Engagement question]
[...continue for 5-7 days]
## Newsletter Segment
[Summary paragraph with link]
Step 4: Save
Save to content/social/schedules/[YYYY-MM-DD]-[slug]-schedule.md.
Rules
- Every social post must work without context — do not assume the reader saw the blog post.
- No post should be a verbatim copy of a section from the blog. Rephrase for the platform.
- Questions outperform statements for engagement. Include at least one question post.
- Threads should hook with the most compelling point, not "Thread on [topic]."
- Include platform-appropriate formatting (line breaks for readability on Twitter, paragraphs for LinkedIn).
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 · 83 lines · 0 tokens per session scan A 58f0356e9ca4
schedule 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 562 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.
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.
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.