Borrowing it
Nothing to install: this file belongs to dsifry/metaswarm. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dsifry/metaswarm/main/.claude/commands/prime.mdgit clone --depth 1 https://github.com/dsifry/metaswarmWrote 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/dsifry/metaswarm/prime)<a href="https://agentmods.dev/commands/dsifry/metaswarm/prime"><img src="https://agentmods.dev/badge/commands/dsifry/metaswarm/prime/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/dsifry/metaswarm/prime"><img src="https://agentmods.dev/badge/commands/dsifry/metaswarm/prime.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 | $0.00010 | $0.01544 |
| Opus 5.5 | $0.00004 | $0.00618 |
| Sonnet 5.5 | $0.00002 | $0.00309 |
| Haiku 4.5 | $0.00001 | $0.00154 |
Grade A, and why
prime 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 1mo 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BEADS Prime
CRITICAL: Run this command at the START of any investigation, planning, or implementation work to load relevant knowledge into your context.
When to Use
- Starting work on a GitHub Issue
- Beginning investigation/research
- Before writing a plan
- Before implementing changes
- When switching to a new area of the codebase
How It Works
This command queries the BEADS knowledge base for facts relevant to your current context and injects them into the conversation, ensuring you:
- Follow established patterns and rules
- Avoid known gotchas and pitfalls
- Make decisions aligned with architectural choices
- Don't repeat mistakes that have been learned from
Usage
Quick Prime (Most Common)
For general context with automatic detection:
bd prime
Prime for Specific Files
When working on specific files:
bd prime --files "src/lib/services/**/*.ts" "src/api/routes/**/*.ts"
Prime for Keywords
When working on a specific topic:
bd prime --keywords "authentication" "jwt" "security"
Prime for Work Type
When doing a specific type of work:
bd prime --work-type planning
bd prime --work-type implementation
bd prime --work-type review
bd prime --work-type debugging
Prime for Context Recovery
When resuming after context compaction or in a new session:
bd prime --work-type recovery
This loads active plan, project context, execution state, and relevant knowledge base facts. See "Context Recovery" section below.
Combined
bd prime \
--files "src/lib/services/ai-*.ts" \
--keywords "ai" "provider" "openai" \
--work-type implementation
What Gets Loaded
1. MUST FOLLOW (Critical Rules)
Non-negotiable rules containing NEVER/ALWAYS/MUST:
- "NEVER use
as anytype casting" - "ALWAYS use centralized AI config"
- Security-critical patterns
2. GOTCHAS (Common Pitfalls)
Known issues to avoid:
- "Truthy check fails for explicit zero values - use !== undefined"
- API behavior quirks
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.
- 1mo ago First seen · 260 lines · 10 tokens per session scan A 8fc65af9e932
prime is a command published in the GitHub repository dsifry/metaswarm (421 stars, last pushed 4mo ago), licensed MIT. It adds 10 tokens to every session and 1,544 once invoked, about $0.0000 per session on Opus 5.5. 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 2026-08-30.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
memory-store
Store an insight, decision, or pattern to memory.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
lians-recall
Recall current (non-stale) facts from Lians memory, optionally as-of a past date.