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 commands/ethanolivertroy/my-agent-stuff/parallel-researchgit clone --depth 1 https://github.com/ethanolivertroy/my-agent-stuffWrote 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/commands/ethanolivertroy/my-agent-stuff/parallel-research)<a href="https://agentmods.dev/commands/ethanolivertroy/my-agent-stuff/parallel-research"><img src="https://agentmods.dev/badge/commands/ethanolivertroy/my-agent-stuff/parallel-research.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 | $0.00004 | $0.00508 |
| Opus 5 | $0.00002 | $0.00254 |
| Sonnet 5 | $0.00001 | $0.00102 |
| Haiku 4.5 | $0.00000 | $0.00051 |
Grade A, and why
parallel-research 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.
What it actually says
Launch parallel research subagents to build a grounded answer to the current question or decision.
Use fresh context, not forked context, unless I explicitly ask for forked context. Researchers and scouts should inspect sources directly instead of relying on the main conversation history.
Use a combination of researcher and scout subagents:
- Use
researcherfor web, docs, standards, ecosystem, recent changes, benchmarks, and primary-source evidence. - Use
scoutfor local codebase context, existing implementation patterns, repo constraints, and files that would be affected.
Give each subagent a distinct angle. Unless I specify angles, use these three:
-
External evidence Use
researcherto find current, authoritative sources: official docs, specs, release notes, benchmarks, issue threads, or primary explanations. -
Local code context Use
scoutto inspect the repository for relevant files, existing patterns, constraints, tests, and likely integration points. -
Practical tradeoffs Use
researcherorscout, whichever fits the question, to compare options, risks, edge cases, maintenance cost, and what would be easiest to validate.
Adapt the angles when the question calls for it:
- Library/API questions: include official docs and recent examples.
- Architecture decisions: include local module boundaries, dependency direction, and migration cost.
- Debugging questions: include likely failure modes, local call paths, and exact error evidence.
- UI/product questions: include user flow, accessibility, design precedent, and implementation constraints.
- Time-sensitive topics: include a recent-developments angle and prefer 2026/2025 sources.
Prefer two or three strong subagents over many vague ones. The parent agent should frame the question and assign angles; the child agents should research or scout, not invent broad plans.
Ask each subagent to return concise findings with evidence:
- file paths and line ranges for local findings
- source links for external findings
- confidence level and gaps
- recommended next step or decision implication
Do not ask subagents to edit files. This is a research pass only unless I explicitly ask for implementation.
After the subagents return, synthesize the answer into:
- what we know
- what the local codebase implies
- tradeoffs and risks
- gaps or assumptions
- the recommended next move
If findings disagree, call out the disagreement instead of smoothing it over.
$@
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 · 51 lines · 4 tokens per session scan A 7a279437a1ec
parallel-research is a command published in the GitHub repository ethanolivertroy/my-agent-stuff (11 stars, last pushed 1mo ago), licensed MIT. It adds 4 tokens to every session and 508 once invoked, about $0.0000 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 2026-08-30.
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