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Get Started Free →Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent.
.claude/skills/yogsoth-ai-spawn-agent/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | -33% | 0% |
| case-14 | ✗→✓ | ▲ Improved | -49% | 0% |
| case-06 | ✗→✓ | ▲ Improved | -53% | 0% |
| case-07 | ✗→✓ | ▲ Improved | -38% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -28% | 0% |
When an SOP declares execution: subagent in its frontmatter, this skill governs how main CC creates and invokes that subagent.
| Dimension | Default | |-----------|---------| | Model | opus | | Tools | all (subagent inherits main CC's full MCP access) | | Output | markdown |
When you encounter an SOP with execution: subagent:
Read the file specified in the SOP's prompt frontmatter field (relative to the SOP directory).
Take the SOP's input parameters and format as:
[FIELD_NAME]:
[value]
[FIELD_NAME]:
[value]Each field on its own line, separated by blank lines. Field names in UPPER_CASE.
Agent({
description: "[SOP name] — [brief task description]",
prompt: "[prompt.md content]\n\n---\n\n[formatted user message]",
model: "[opus, unless SOP overrides]"
})The subagent's prompt combines:
---)The Agent tool result IS the SOP output. Pass it back to the calling tactic/strategy as-is. No parsing, no transformation.
If the SOP frontmatter contains override fields:
model: sonnet → use model: "sonnet" in Agent calltools: [alphaxiv, ss] → add tool restriction note to the promptWhen a tactic needs multiple subagents (e.g., debate with Critic + Defender), spawn them as parallel Agent tool calls in a single message. The Agent tool natively supports this.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 8,104 | 33,665 | +315% | 1 | 1 | 0% | 1,129 | 3,590 | +218% | 0 | 0 | — |
case-02 | fail→fail | 11,252 | 14,835 | +32% | 1 | 1 | 0% | 561 | 1,350 | +141% | 0 | 0 | — |
case-03 | fail→fail | 49,834 | 8,664 | -83% | 1 | 1 | 0% | 5,421 | 1,111 | -80% | 0 | 0 | — |
case-04 | fail→pass | 17,596 | 8,304 | -53% | 1 | 1 | 0% | 1,210 | 813 | -33% | 0 | 0 | — |
case-14 | fail→pass | 15,341 | 7,548 | -51% | 1 | 1 | 0% | 1,789 | 906 | -49% | 0 | 0 | — |
case-05 | pass→pass | 10,892 | 2,338 | -79% | 1 | 1 | 0% | 978 | 823 | -16% | 0 | 0 | — |
case-06 | fail→pass | 16,999 | 8,510 | -50% | 1 | 1 | 0% | 2,125 | 996 | -53% | 0 | 0 | — |
case-07 | fail→pass | 13,324 | 7,719 | -42% | 1 | 1 | 0% | 1,455 | 905 | -38% | 0 | 0 | — |
case-08 | fail→pass | 12,670 | 8,560 | -32% | 1 | 1 | 0% | 1,341 | 959 | -28% | 0 | 0 | — |
case-15 | pass→pass | 10,225 | 6,926 | -32% | 1 | 1 | 0% | 918 | 807 | -12% | 0 | 0 | — |
case-09 | pass→pass | 16,485 | 7,455 | -55% | 1 | 1 | 0% | 1,780 | 820 | -54% | 0 | 0 | — |
case-10 | fail→pass | 17,334 | 7,238 | -58% | 1 | 1 | 0% | 2,018 | 752 | -63% | 0 | 0 | — |
case-11 | fail→fail | 13,149 | 6,927 | -47% | 1 | 1 | 0% | 1,226 | 750 | -39% | 0 | 0 | — |
case-12 | pass→pass | 9,725 | 7,567 | -22% | 1 | 1 | 0% | 751 | 777 | +3% | 0 | 0 | — |
case-13 | fail→pass | 16,884 | 2,618 | -84% | 1 | 1 | 0% | 1,184 | 845 | -29% | 0 | 0 | — |
case-16 | pass→pass | 13,166 | 6,847 | -48% | 1 | 1 | 0% | 1,258 | 690 | -45% | 0 | 0 | — |
case-17 | fail→pass | 15,094 | 7,549 | -50% | 1 | 1 | 0% | 1,877 | 889 | -53% | 0 | 0 | — |
case-18 | fail→pass | 14,916 | 7,264 | -51% | 1 | 1 | 0% | 1,484 | 724 | -51% | 0 | 0 | — |
case-19 | fail→pass | 10,555 | 7,301 | -31% | 1 | 1 | 0% | 904 | 780 | -14% | 0 | 0 | — |
case-20 | fail→pass | 18,409 | 7,298 | -60% | 1 | 1 | 0% | 2,043 | 855 | -58% | 0 | 0 | — |
case-21 | pass→fail | 21,526 | 2,766 | -87% | 1 | 1 | 0% | 1,799 | 876 | -51% | 0 | 0 | — |
case-22 | pass→pass | 8,066 | 2,968 | -63% | 1 | 1 | 0% | 480 | 902 | +88% | 0 | 0 | — |
case-23 | pass→pass | 17,725 | 13,985 | -21% | 1 | 1 | 0% | 2,295 | 2,013 | -12% | 0 | 0 | — |
case-24 | pass→pass | 17,184 | 9,592 | -44% | 1 | 1 | 0% | 2,212 | 2,138 | -3% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 24 cases were attempted, and 22 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +42 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.