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 mattmre/EVOKORE-MCP-PUBLIC --skill agent-spawngit clone --depth 1 https://github.com/mattmre/EVOKORE-MCP-PUBLICWrote 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/mattmre/evokore-mcp-public/agent-spawn)<a href="https://agentmods.dev/skills/mattmre/evokore-mcp-public/agent-spawn"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/agent-spawn/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/mattmre/evokore-mcp-public/agent-spawn"><img src="https://agentmods.dev/badge/skills/mattmre/evokore-mcp-public/agent-spawn.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 | $0.00028 | $0.00415 |
| Opus 5.5 | $0.00011 | $0.00166 |
| Sonnet 5.5 | $0.00006 | $0.00083 |
| Haiku 4.5 | $0.00003 | $0.00042 |
Grade A, and why
agent-spawn 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
/agent-spawn — Spawn Specialist Sub-Agent
Delegates a specific task to a specialist sub-agent, keeping the main session context clean.
Usage
/agent-spawn "researcher" "Find all usages of TrustLedger in src/"
/agent-spawn "implementer" "Implement the score decay function in src/TrustLedger.ts"
/agent-spawn "tester" "Write vitest tests for pattern-extractor.js"
Available Archetypes
| Archetype | Domain | Best for |
|---|---|---|
| researcher | research | Codebase analysis, dependency tracing |
| implementer | execution | Feature implementation, bug fixes |
| tester | quality | Test writing, coverage analysis |
| reviewer | quality | Code review, security audit |
| architect | orchestration | Design decisions, API design |
| debugger | execution | Root cause analysis, bug investigation |
What it does
- Creates an Agent tool call with the specified subagent_type
- Passes the task description and relevant context
- The sub-agent runs in isolation and returns a result
- Result is summarized in the main session context
Best practices
- Use researcher before implementer (plan before code)
- Keep sub-agent prompts self-contained (include file paths, context)
- Use isolation: worktree for implementers that write code
- Prefer sequential spawning to avoid worktree race conditions
Integration
- Works with AGT-019 (Claims Coordinator) for resource claim management
- Sub-agent results are captured in session-replay log
- SessionAnalyticsManager tracks subagent counts per session
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 · 53 lines · 28 tokens per session scan A bebd31eb6410
agent-spawn is a skill published in the GitHub repository mattmre/EVOKORE-MCP-PUBLIC (3 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 415 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 2026-09-03.
Other skills, from other repositories
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starting-a-new-project
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managing-mcp-servers
Use when the user asks to add, change, remove, enable or disable an MCP server, or when an MCP tool is missing, needs sign-in, fails, or was blocked. ThinkRail runs pi in-process, so there is no pi command to call.
todos
Use when the user asks for a shared plan, a task needs at least three substantive execution steps, or a loose TODO is pending. Without an explicit plan request, not for one-shot answers or checks, or one- to two-step work that is not already in the list.
asking-user-questions
Use when composing an askuserquestion round inside a workflow, or when a workflow skill names it at a question step. Shared norms for the tool — not a workflow, nothing to execute.