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-reviewergit 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-reviewer)<a href="https://agentmods.dev/skills/ayushcodes10/echo-mem/source-command-sparc-reviewer"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-reviewer/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-reviewer"><img src="https://agentmods.dev/badge/skills/ayushcodes10/echo-mem/source-command-sparc-reviewer.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 | $0.00018 | $0.00333 |
| Opus 5.5 | $0.00007 | $0.00133 |
| Sonnet 5.5 | $0.00004 | $0.00067 |
| Haiku 4.5 | $0.00002 | $0.00033 |
Grade A, and why
source-command-sparc-reviewer 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.
What it actually says
source-command-sparc-reviewer
Use this skill when the user asks to run the migrated source command sparc-reviewer.
Command Template
SPARC Reviewer Mode
Purpose
Code review using batch file analysis for comprehensive reviews.
Activation
Option 1: Using MCP Tools (Preferred in Codex)
mcp__claude-flow__sparc_mode {
mode: "reviewer",
task_description: "review pull request #123",
options: {
security_check: true,
performance_check: true
}
}
Option 2: Using NPX CLI (Fallback when MCP not available)
# Use when running from terminal or MCP tools unavailable
npx Codex-flow sparc run reviewer "review pull request #123"
# For alpha features
npx Codex-flow@alpha sparc run reviewer "review pull request #123"
Option 3: Local Installation
# If Codex-flow is installed locally
./Codex-flow sparc run reviewer "review pull request #123"
Core Capabilities
- Code quality assessment
- Security review
- Performance analysis
- Best practices check
- Documentation review
Review Criteria
- Code correctness
- Design patterns
- Error handling
- Test coverage
- Maintainability
Batch Analysis
- Parallel file review
- Pattern detection
- Dependency checking
- Consistency validation
- Automated reporting
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 · 66 lines · 18 tokens per session scan A d286592da399
source-command-sparc-reviewer is a skill published in the GitHub repository ayushcodes10/echo-mem (2 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 333 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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