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 agentmods add skills/zpower426/datapowers/subagent-driven-analysisnpx skills add zpower426/datapowers --skill subagent-driven-analysisgit clone --depth 1 https://github.com/zpower426/datapowersWrote 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/zpower426/datapowers/subagent-driven-analysis)<a href="https://agentmods.dev/skills/zpower426/datapowers/subagent-driven-analysis"><img src="https://agentmods.dev/badge/skills/zpower426/datapowers/subagent-driven-analysis.svg" alt="Measured on agentmods" 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 | $0.00035 | $0.01713 |
| Opus 5 | $0.00017 | $0.00856 |
| Sonnet 5 | $0.00007 | $0.00343 |
| Haiku 4.5 | $0.00003 | $0.00171 |
Grade A, and why
subagent-driven-analysis 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 4d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Subagent-Driven Analysis
Execute analysis plans by dispatching fresh subagents per task. Two-stage review after each task: statistical correctness first, then code quality.
Why subagents: Each analysis task gets a fresh agent with only the context it needs. This prevents context pollution between tasks, keeps each agent focused, and produces independently reviewable outputs.
When to Use
digraph when {
"Have an analysis plan?" [shape=diamond];
"Tasks mostly independent?" [shape=diamond];
"subagent-driven-analysis" [shape=box];
"executing-plans manually" [shape=box];
"Brainstorm + write plan first" [shape=box];
"Have an analysis plan?" -> "Tasks mostly independent?" [label="yes"];
"Have an analysis plan?" -> "Brainstorm + write plan first" [label="no"];
"Tasks mostly independent?" -> "subagent-driven-analysis" [label="yes"];
"Tasks mostly independent?" -> "executing-plans manually" [label="no, tightly coupled"];
}
The Process
digraph process {
"Read plan, extract all tasks, create TodoWrite" [shape=box];
"More tasks?" [shape=diamond];
"Dispatch analyst subagent" [shape=box];
"Subagent needs context?" [shape=diamond];
"Provide context, re-dispatch" [shape=box];
"Subagent completes task" [shape=box];
"Dispatch statistical reviewer" [shape=box];
"Statistical review passes?" [shape=diamond];
"Subagent fixes issues" [shape=box];
"Dispatch code quality reviewer" [shape=box];
"Code quality passes?" [shape=diamond];
"Mark task complete" [shape=box];
"Final analysis review" [shape=box];
"Done" [shape=doublecircle];
"Read plan, extract all tasks, create TodoWrite" -> "More tasks?";
"More tasks?" -> "Dispatch analyst subagent" [label="yes"];
"More tasks?" -> "Final analysis review" [label="no"];
"Dispatch analyst subagent" -> "Subagent needs context?";
"Subagent needs context?" -> "Provide context, re-dispatch" [label="yes"];
"Provide context, re-dispatch" -> "Dispatch analyst subagent";
"Subagent needs context?" -> "Subagent completes task" [label="no"];
"Subagent completes task" -> "Dispatch statistical reviewer";
"Dispatch statistical reviewer" -> "Statistical review passes?";
"Statistical review passes?" -> "Subagent fixes issues" [label="no"];
"Subagent fixes issues" -> "Dispatch statistical reviewer" [label="re-review"];
"Statistical review passes?" -> "Dispatch code quality reviewer" [label="yes"];
"Dispatch code quality reviewer" -> "Code quality passes?";
"Code quality passes?" -> "Subagent fixes issues" [label="no"];
"Subagent fixes issues" -> "Dispatch code quality reviewer" [label="re-review"];
"Code quality passes?" -> "Mark task complete" [label="yes"];
"Mark task complete" -> "More tasks?";
"Final analysis review" -> "Done";
}
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 190 lines · 35 tokens per session scan A 1648539ca88e
subagent-driven-analysis is a skill published in the GitHub repository zpower426/datapowers (1 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 1,713 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
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