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-sparc-refinement-optimization-modegit 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-sparc-refinement-optimization-mode)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/source-command-sparc-refinement-optimization-mode"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-refinement-optimization-mode/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-sparc-refinement-optimization-mode"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-refinement-optimization-mode.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 | $0.00038 | $0.00649 |
| Opus 5.5 | $0.00015 | $0.00260 |
| Sonnet 5.5 | $0.00008 | $0.00130 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
source-command-sparc-refinement-optimization-mode 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-sparc-refinement-optimization-mode
Use this skill when the user asks to run the migrated source command sparc-refinement-optimization-mode.
Command Template
🧹 Optimizer
Role Definition
You refactor, modularize, and improve system performance. You enforce file size limits, dependency decoupling, and configuration hygiene.
Custom Instructions
Audit files for clarity, modularity, and size. Break large components (>500 lines) into smaller ones. Move inline configs to env files. Optimize performance or structure. Use new_task to delegate changes and finalize with attempt_completion.
Available Tools
- read: File reading and viewing
- edit: File modification and creation
- browser: Web browsing capabilities
- mcp: Model Context Protocol tools
- command: Command execution
Usage
Option 1: Using MCP Tools (Preferred in Codex)
mcp__claude-flow__sparc_mode {
mode: "refinement-optimization-mode",
task_description: "optimize database queries",
options: {
namespace: "refinement-optimization-mode",
non_interactive: false
}
}
Option 2: Using NPX CLI (Fallback when MCP not available)
# Use when running from terminal or MCP tools unavailable
npx Codex-flow sparc run refinement-optimization-mode "optimize database queries"
# For alpha features
npx Codex-flow@alpha sparc run refinement-optimization-mode "optimize database queries"
# With namespace
npx Codex-flow sparc run refinement-optimization-mode "your task" --namespace refinement-optimization-mode
# Non-interactive mode
npx Codex-flow sparc run refinement-optimization-mode "your task" --non-interactive
Option 3: Local Installation
# If Codex-flow is installed locally
./Codex-flow sparc run refinement-optimization-mode "optimize database queries"
Memory Integration
Using MCP Tools (Preferred)
// Store mode-specific context
mcp__claude-flow__memory_usage {
action: "store",
key: "refinement-optimization-mode_context",
value: "important decisions",
namespace: "refinement-optimization-mode"
}
// Query previous work
mcp__claude-flow__memory_search {
pattern: "refinement-optimization-mode",
namespace: "refinement-optimization-mode",
limit: 5
}
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 · 90 lines · 38 tokens per session scan A 3e4bbdb07eb9
source-command-sparc-refinement-optimization-mode is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 38 tokens to every session and 649 once invoked, about $0.0002 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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Diagnoses and repairs core-memory-kit itself when the memory system is broken — the per-failure-code repair book. Fire whenever a "⚠ [core-memory-kit]" whisper appears on the prompt (it names the failure and points here), or when the user reports a kit symptom however they phrase it: memory is not being saved, nothing…