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 skills add ayushcodes10/echo-mem --skill source-command-swarm-researchgit 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/skills/ayushcodes10/echo-mem/source-command-swarm-research)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/source-command-swarm-research"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-swarm-research/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/skills/ayushcodes10/echo-mem/source-command-swarm-research"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-swarm-research.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 | $0.00017 | $0.00847 |
| Opus 5.5 | $0.00007 | $0.00339 |
| Sonnet 5.5 | $0.00003 | $0.00169 |
| Haiku 4.5 | $0.00002 | $0.00085 |
Grade A, and why
source-command-swarm-research 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-swarm-research
Use this skill when the user asks to run the migrated source command swarm-research.
Command Template
Research Swarm Strategy
Purpose
Deep research through parallel information gathering.
Activation
Using MCP Tools
// Initialize research swarm
mcp__claude-flow__swarm_init({
"topology": "mesh",
"maxAgents": 6,
"strategy": "adaptive"
})
// Orchestrate research task
mcp__claude-flow__task_orchestrate({
"task": "research topic X",
"strategy": "parallel",
"priority": "medium"
})
Using CLI (Fallback)
npx Codex-flow swarm "research topic X" --strategy research
Agent Roles
Agent Spawning with MCP
// Spawn research agents
mcp__claude-flow__agent_spawn({
"type": "researcher",
"name": "Web Researcher",
"capabilities": ["web-search", "content-extraction", "source-validation"]
})
mcp__claude-flow__agent_spawn({
"type": "researcher",
"name": "Academic Researcher",
"capabilities": ["paper-analysis", "citation-tracking", "literature-review"]
})
mcp__claude-flow__agent_spawn({
"type": "analyst",
"name": "Data Analyst",
"capabilities": ["data-processing", "statistical-analysis", "visualization"]
})
mcp__claude-flow__agent_spawn({
"type": "documenter",
"name": "Report Writer",
"capabilities": ["synthesis", "technical-writing", "formatting"]
})
Research Methods
Information Gathering
// Parallel information collection
mcp__claude-flow__parallel_execute({
"tasks": [
{ "id": "web-search", "command": "search recent publications" },
{ "id": "academic-search", "command": "search academic databases" },
{ "id": "data-collection", "command": "gather relevant datasets" }
]
})
// Store research findings
mcp__claude-flow__memory_usage({
"action": "store",
"key": "research-findings-" + Date.now(),
"value": JSON.stringify(findings),
"namespace": "research",
"ttl": 604800 // 7 days
})
Analysis and Validation
// Pattern recognition in findings
mcp__claude-flow__pattern_recognize({
"data": researchData,
"patterns": ["trend", "correlation", "outlier"]
})
// Cognitive analysis
mcp__claude-flow__cognitive_analyze({
"behavior": "research-synthesis"
})
// Cross-reference validation
mcp__claude-flow__quality_assess({
"target": "research-sources",
"criteria": ["credibility", "relevance", "recency"]
})
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 · 148 lines · 17 tokens per session scan A 885b8f3ef427
source-command-swarm-research is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 17 tokens to every session and 847 once invoked, about $0.0001 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 2026-09-12.
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