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 matteotitta/genesys-skills --skill batch-rungit clone --depth 1 https://github.com/matteotitta/genesys-skillsWrote 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/matteotitta/genesys-skills/batch-run)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/batch-run"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/batch-run/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/matteotitta/genesys-skills/batch-run"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/batch-run.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 | $0.00136 | $0.01817 |
| Opus 5.5 | $0.00054 | $0.00727 |
| Sonnet 5.5 | $0.00027 | $0.00363 |
| Haiku 4.5 | $0.00014 | $0.00182 |
Grade A, and why
batch-run 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 1mo 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/batch-run — Fan Out Any Skill Across N Entities
Dispatches N parallel subagents to run the same skill across a list of entities, with shared upstream context injected into each run.
Claude Code Triggers
Invoke when user says:
- "/batch-run --entities 'a,b,c'"
- "Run product-messaging for all 8 ClientCo products"
- "Fan out competitor-research across these 5 competitors"
- "Parallelize landing-page-copy across home, pricing, about"
- "Run [skill] for each of [list]"
Do NOT invoke when:
- User wants a single skill run (invoke the skill directly)
- User wants a sequential chain (use
/website-buildor workflow-design) - Entities have cross-dependencies (shared state breaks parallelization)
Input Format
/batch-run <skill-name> \
--entities "entity1, entity2, entity3" \
[--client <slug>] \
[--context <path-to-upstream-output>] \
[--output-dir <path>] \
[--max-parallel <N>]
Required:
<skill-name>— must exist in skill-catalog (e.g.,product-messaging,competitor-research)--entities— comma-separated list of entity names
Optional:
--client— client slug for folder routing (e.g.,ClientCo,ClientCo)--context— path to upstream deliverable that provides shared context (e.g., positioning doc)--output-dir— override default output location--max-parallel— cap concurrent agents (default: 5, max: 10)
Execution Workflow
Phase 1: Validate inputs
- Check
<skill-name>exists in.claude/skills/— fail fast if unknown - Read the skill's SKILL.md to extract:
- Required dependencies (upstream skills)
- Output type + default location
- Review gate level
- Verify
--contextfile exists if provided - Resolve
--clientslug against.claude/rules/consulting-clients.mdfolder structure
Phase 2: Build shared context package
For each subagent, the context package contains:
- Skill SKILL.md — the full skill instructions
- Shared upstream context — from
--contextflag or auto-detected (e.g., positioning.md in client folder) - Entity-specific input — the current entity name + any entity-specific context in the client folder (e.g.,
projects/consulting/ClientCo/docs/treasury.md) - Client CLAUDE.md — voice, brand, quality bar
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.
- 1mo ago First seen · 213 lines · 136 tokens per session scan A d14ca6a855be
batch-run is a skill published in the GitHub repository matteotitta/genesys-skills (46 stars, last pushed 11d ago), licensed MIT. It adds 136 tokens to every session and 1,817 once invoked, about $0.0005 per session on Opus 5.5. 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.
Other skills, from other repositories
category-point-of-view
Create a differentiated B2B category point of view that leads with the customer problem, defines the market shift, names the category or strategic frame, and turns it into content, distribution, and measurement guidance.
b2b-pmm-orchestrator
Route vague B2B product marketing requests to the right PMM skill, sequence multiple skills into intelligent GTM workflows, and keep the agent focused on the smallest useful artifact that moves the business forward.
ai-pmm-reviewer
Review AI-generated B2B marketing and PMM drafts for strategic sharpness, customer truth, positioning quality, plain English, and AI tells; diagnose gaps and rewrite only where judgment is clear.
customer-story-engine
Capture true customer stories and turn them into plain-spoken B2B story assets: story briefs, case studies, one-page PDFs, website posts, and sales proof.
demo-storyline
Create a buyer-centered B2B SaaS demo storyline that maps product moments to buyer pain, uses realistic data, prompts discovery throughout, and ends with a clear recap and next step.
sales-narrative-deck
Create a sales-ready B2B narrative deck outline that starts with buyer pain, teaches the market, shows the solution, supports a demo, and gives reps a clear path to proof, pricing, competition, recap, and next steps.