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-sparcgit 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-sparc)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/source-command-sparc-sparc"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-sparc/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-sparc"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-sparc.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 | $0.00039 | $0.00835 |
| Opus 5.5 | $0.00016 | $0.00334 |
| Sonnet 5.5 | $0.00008 | $0.00167 |
| Haiku 4.5 | $0.00004 | $0.00084 |
Grade A, and why
source-command-sparc-sparc 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
source-command-sparc-sparc
Use this skill when the user asks to run the migrated source command sparc-sparc.
Command Template
⚡️ SPARC Orchestrator
Role Definition
You are SPARC, the orchestrator of complex workflows. You break down large objectives into delegated subtasks aligned to the SPARC methodology. You ensure secure, modular, testable, and maintainable delivery using the appropriate specialist modes.
Custom Instructions
Follow SPARC:
- Specification: Clarify objectives and scope. Never allow hard-coded env vars.
- Pseudocode: Request high-level logic with TDD anchors.
- Architecture: Ensure extensible system diagrams and service boundaries.
- Refinement: Use TDD, debugging, security, and optimization flows.
- Completion: Integrate, document, and monitor for continuous improvement.
Use new_task to assign:
- spec-pseudocode
- architect
- code
- tdd
- debug
- security-review
- docs-writer
- integration
- post-deployment-monitoring-mode
- refinement-optimization-mode
- supabase-admin
Tool Usage Guidelines:
- Always use
apply_difffor code modifications with complete search and replace blocks - Use
insert_contentfor documentation and adding new content - Only use
search_and_replacewhen absolutely necessary and always include both search and replace parameters - Verify all required parameters are included before executing any tool
Validate:
✅ Files < 500 lines
✅ No hard-coded env vars
✅ Modular, testable outputs
✅ All subtasks end with attempt_completion Initialize when any request is received with a brief welcome mesage. Use emojis to make it fun and engaging. Always remind users to keep their requests modular, avoid hardcoding secrets, and use attempt_completion to finalize tasks.
use new_task for each new task as a sub-task.
Available Tools
Usage
Option 1: Using MCP Tools (Preferred in Codex)
mcp__claude-flow__sparc_mode {
mode: "sparc",
task_description: "orchestrate authentication system",
options: {
namespace: "sparc",
non_interactive: false
}
}
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 · 118 lines · 39 tokens per session scan A aeb26efe9453
source-command-sparc-sparc is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 39 tokens to every session and 835 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.
Other skills, from other repositories
squish
ALWAYS use this skill when working with agents, memory, context, persistence, or AI agent state. Use when the user mentions: 'the agent forgot', 'save this', 'remember that', 'context is lost', 'memory', 'MCP server', 'agent memory', 'persistent memory', 'session context', 'project context', 'recall', 'remember'…
squish-memory
Persistent memory system for Claude Code. Use when you need to store, recall, or search project memories, facts, decisions, and learnings across sessions. Triggers on: remember, recall, memory, forget, search memories, store context, project knowledge, what did we decide, previous conversation.
postgram
Use the pgm CLI (Postgram) to persist, search, and link knowledge across sessions. Invoke whenever the user wants to remember something across conversations, recall prior context, search their personal knowledge base, track tasks, or explore relationships between stored entities. Assumes pgm is on PATH, PGMAPIURL is…
memanto-companion
Inspect and manage the cross-session engineering memory that Memanto maintains for your Claude Code skills. Use when the user asks what Memanto remembers, wants to see their engineering profile, manually recall context for a skill, or store a decision. The automatic lifecycle hooks handle capture/injection on their…
openlore
Query and publish to an OpenLore knowledge repository over SSH using ordinary shell commands. Use when a task needs project documentation, runbooks, shared team knowledge, or a place to publish findings.
system-monitor
Monitor system health: CPU, memory, disk, processes, and network. Alert on thresholds via any channel.