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 jmagly/aiwg --skill parallel-dispatchgit clone --depth 1 https://github.com/jmagly/aiwgWrote 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/jmagly/aiwg/parallel-dispatch)<a href="https://agentmods.dev/skills/jmagly/aiwg/parallel-dispatch"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/parallel-dispatch/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/jmagly/aiwg/parallel-dispatch"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/parallel-dispatch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00023 | $0.01565 |
| Opus 5 | $0.00012 | $0.00783 |
| Sonnet 5 | $0.00005 | $0.00313 |
| Haiku 4.5 | $0.00002 | $0.00156 |
Grade A, and why
parallel-dispatch 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 9d 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 — 277 lines — stays where its author put it; the contents beside it link to each section on GitHub.
parallel-dispatch
Generic parallel agent orchestration utility for launching multiple agents concurrently.
Triggers
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
- "fan out" → parallel agent dispatch shorthand
- "run all [N] in parallel" → explicit parallel execution
Purpose
This skill provides the foundational infrastructure for launching multiple agents in parallel, collecting their results, and handling timeouts. It is used by higher-level skills like artifact-orchestration, review-synthesis, and gate-evaluation.
Behavior
When triggered, this skill:
-
Parses agent configuration:
- Agent names (from built-in or custom)
- Prompt templates for each agent
- Shared context/artifact reference
- Timeout settings
-
Prepares agent-specific prompts:
- Loads prompt template per agent
- Injects shared context (artifact path, requirements)
- Adds output format requirements
-
Launches agents in parallel:
- Uses single message with multiple Task tool calls
- Each agent runs independently
- No inter-agent communication during execution
-
Collects results:
- Waits for all agents or timeout
- Captures success/failure per agent
- Structures results for downstream processing
-
Returns consolidated results:
- Per-agent output
- Execution metadata (duration, status)
- Aggregated insights (if configured)
Configuration Format
dispatch:
name: "artifact-review"
timeout: 300 # seconds
agents:
- name: security-architect
prompt: |
Review the artifact at {artifact_path} for security concerns.
Focus on: authentication, authorization, data protection, input validation.
Output format: structured findings with severity ratings.
- name: test-architect
prompt: |
Review the artifact at {artifact_path} for testability.
Focus on: test coverage gaps, edge cases, integration points.
Output format: test recommendations with priority.
- name: requirements-analyst
prompt: |
Review the artifact at {artifact_path} for requirements traceability.
Focus on: requirement coverage, gaps, conflicts.
Output format: traceability assessment.
context:
artifact_path: ".aiwg/architecture/sad.md"
requirements_path: ".aiwg/requirements/"
result_format: structured # or 'raw'
aggregate: true # combine findings
What ships with it
1 file 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.
- 9d ago First seen · 277 lines · 23 tokens per session scan A eeca9f713167
parallel-dispatch is a skill published in the GitHub repository jmagly/aiwg (211 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 1,565 once invoked, about $0.0001 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 2026-09-03.
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