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 divingsbysangam/salesforce-compound-engineering-plugin --skill dispatching-parallel-personasgit clone --depth 1 https://github.com/divingsbysangam/salesforce-compound-engineering-pluginWrote 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/divingsbysangam/salesforce-compound-engineering-plugin/dispatching-parallel-personas)<a href="https://agentmods.dev/skills/divingsbysangam/salesforce-compound-engineering-plugin/dispatching-parallel-personas"><img src="https://agentmods.dev/badge/skills/divingsbysangam/salesforce-compound-engineering-plugin/dispatching-parallel-personas.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 5.1 | $0.00084 | $0.00557 |
| Opus 5 | $0.00042 | $0.00279 |
| Sonnet 5 | $0.00017 | $0.00111 |
| Haiku 4.5 | $0.00008 | $0.00056 |
Grade A, and why
dispatching-parallel-personas 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 8d 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
Dispatching Parallel Personas
The shared mechanics every workflow skill uses when it says "dispatch these personas." Skills reference this file instead of restating it; each keeps its own pointer to where its personas live.
What personas are
A persona is a prompt asset under a skill's references/personas/<name>.md — not a registered agent. V3.1 is agentless: no standalone agents are registered on any platform. To dispatch a persona, load the persona file's contents and feed them to a general-purpose subagent as its instructions.
How to dispatch
Run each persona as an isolated subagent via the platform's subagent primitive — the Task tool on Claude Code. On Claude Code these run in parallel, each with isolated context; that isolation is the point of splitting them. On harnesses without a subagent primitive, apply each persona's prompt inline, one after another, against the matching files.
Same-response parallelism rule
To actually run in parallel, issue all dispatches in the same response — one message containing multiple Task calls. One dispatch per response is sequential, not parallel. This is the most common mistake: personas that were meant to run concurrently end up serialized because each Task call went out in its own turn.
Same-file-conflict check
Before dispatching personas that may write files, check whether two of them would edit the same file (e.g. the same trigger handler or LWC component). If so, serialize them, or have one build on the other's committed result — parallel isolated workers editing one file still produce diverging copies that need a real merge. Read-only review and research personas never conflict, so dispatch them all at once.
Prompt quality
Give each persona a bounded packet: the persona file's contents + the specific target files or diff + exactly what to return. Do not tell a persona to "read the whole repo" — scope it to what it needs.
After dispatch
Collect the results, deduplicate across personas (for review, apply sf-review's confidence rubric), and spot-check before trusting. Isolated workers can each surface the same finding or reach a wrong conclusion in isolation — reconcile, don't concatenate.
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.
- 8d ago First seen · 32 lines · 84 tokens per session scan A 191ba18b02d3
dispatching-parallel-personas is a skill published in the GitHub repository divingsbysangam/salesforce-compound-engineering-plugin (10 stars, last pushed 4d ago), licensed MIT. It adds 84 tokens to every session and 557 once invoked, about $0.0004 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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