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/dsifry/metaswarm/primegit clone --depth 1 https://github.com/dsifry/metaswarmWhat 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 | $0.00010 | $0.01544 |
| Opus 5 | $0.00005 | $0.00772 |
| Sonnet 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 3d 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.
- 3d ago First seen · 260 lines · 10 tokens per session scan A 8fc65af9e932
prime is a command published in the GitHub repository dsifry/metaswarm (407 stars, last pushed 2mo ago), licensed MIT. It adds 10 tokens to every session and 1,544 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 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.