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/ayushcodes10/echo-memWrote 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/ayushcodes10/echo-mem/examples)<a href="https://agentmods.dev/commands/ayushcodes10/echo-mem/examples"><img src="https://agentmods.dev/badge/commands/ayushcodes10/echo-mem/examples/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/ayushcodes10/echo-mem/examples"><img src="https://agentmods.dev/badge/commands/ayushcodes10/echo-mem/examples.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 | $0.00965 |
| Opus 5 | $0.00000 | $0.00483 |
| Sonnet 5 | $0.00000 | $0.00193 |
| Haiku 4.5 | $0.00000 | $0.00097 |
Grade A, and why
examples 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 yesterday.
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 — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Examples Swarm Strategy
Common Swarm Patterns
Research Swarm
Using MCP Tools
// Initialize research swarm
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 6,
"strategy": "adaptive"
})
// Spawn research agents
mcp__claude-flow__agent_spawn({
"type": "researcher",
"name": "AI Trends Researcher",
"capabilities": ["web-search", "analysis", "synthesis"]
})
// Orchestrate research
mcp__claude-flow__task_orchestrate({
"task": "research AI trends",
"strategy": "parallel",
"priority": "medium"
})
// Monitor progress
mcp__claude-flow__swarm_status({
"swarmId": "research-swarm"
})
Using CLI (Fallback)
npx claude-flow swarm "research AI trends" \
--strategy research \
--mode distributed \
--max-agents 6 \
--parallel
Development Swarm
Using MCP Tools
// Initialize development swarm
mcp__claude-flow__swarm_init({
"topology": "hierarchical",
"maxAgents": 8,
"strategy": "balanced"
})
// Spawn development team
const devAgents = [
{ type: "architect", name: "API Designer" },
{ type: "coder", name: "Backend Developer" },
{ type: "tester", name: "API Tester" },
{ type: "documenter", name: "API Documenter" }
]
devAgents.forEach(agent => {
mcp__claude-flow__agent_spawn({
"type": agent.type,
"name": agent.name,
"swarmId": "dev-swarm"
})
})
// Orchestrate development
mcp__claude-flow__task_orchestrate({
"task": "build REST API",
"strategy": "sequential",
"dependencies": ["design", "implement", "test", "document"]
})
// Enable monitoring
mcp__claude-flow__swarm_monitor({
"swarmId": "dev-swarm",
"interval": 5000
})
Using CLI (Fallback)
npx claude-flow swarm "build REST API" \
--strategy development \
--mode hierarchical \
--monitor \
--output sqlite
Analysis Swarm
Using MCP Tools
// Initialize analysis swarm
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 5,
"strategy": "adaptive"
})
// Spawn analysis agents
mcp__claude-flow__agent_spawn({
"type": "analyst",
"name": "Code Analyzer",
"capabilities": ["static-analysis", "complexity-analysis"]
})
mcp__claude-flow__agent_spawn({
"type": "analyst",
"name": "Security Analyzer",
"capabilities": ["security-scan", "vulnerability-detection"]
})
// Parallel analysis execution
mcp__claude-flow__parallel_execute({
"tasks": [
{ "id": "analyze-code", "command": "analyze codebase structure" },
{ "id": "analyze-security", "command": "scan for vulnerabilities" },
{ "id": "analyze-performance", "command": "identify bottlenecks" }
]
})
// Generate comprehensive report
mcp__claude-flow__performance_report({
"format": "detailed",
"timeframe": "current"
})
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.
- yesterday First seen · 169 lines · 0 tokens per session scan A 61e11e72b616
examples is a command published in the GitHub repository ayushcodes10/echo-mem (1 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 965 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 2026-09-10.
Other commands, from other repositories
memory-recall
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memory-store
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memory-health
Check AutoMem service health and connection status.
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.