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 hugobowne/show-us-your-agent-skills --skill hermes-workflows-creatinggit clone --depth 1 https://github.com/hugobowne/show-us-your-agent-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/hugobowne/show-us-your-agent-skills/hermes-workflows-creating)<a href="https://agentmods.dev/skills/hugobowne/show-us-your-agent-skills/hermes-workflows-creating"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/hermes-workflows-creating/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/hugobowne/show-us-your-agent-skills/hermes-workflows-creating"><img src="https://agentmods.dev/badge/skills/hugobowne/show-us-your-agent-skills/hermes-workflows-creating.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 10 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00049 | $0.01284 |
| Opus 5 | $0.00024 | $0.00642 |
| Sonnet 5 | $0.00010 | $0.00257 |
| Haiku 4.5 | $0.00005 | $0.00128 |
Grade A, and why
hermes-workflows-creating 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 12d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project: skylarbpayne/hermes-workflows. "Code-first durable workflows for agent work, Review Queues, Workflow Workers, and receipts."
License: Apache License 2.0. Full license text is in
LICENSEalongside this file.Snapshot: Frozen copy of
hermes-workflows-creating/SKILL.mdas of 2026-07-03. The maintained version lives upstream and may have evolved since this snapshot.
Hermes Workflows — creating workflows
Use this when designing or implementing a workflow definition. This skill is generic authoring guidance, not a place for project-specific workflow shapes.
Product model
Hermes Workflows are ordinary Python orchestration code with durable execution state.
Use the public authoring primitives:
@workflowfor the durable workflow entrypoint.agent(...)for judgment-heavy or generative work.bash(...)for deterministic local commands and receipts.ask(...)for typed review input and external-action approval gates.parallel(...)for fan-out/fan-in.pipeline(...)for staged transformations over items.goal(...)for loop-until-done semantics when available/appropriate.
Do not expose runtime plumbing (ctx.handoff, raw signals, internal waits, leases, outbox commands) in normal workflow authoring unless debugging the runtime itself.
Authoring checklist
- Define the purpose and side-effect boundary.
- Define typed dataclass inputs and outputs.
- Split steps by ownership:
- agent judgment/synthesis/editing →
agent(...) - deterministic command/check/evidence →
bash(...) - human decision or external side-effect authorization →
ask(...)
- agent judgment/synthesis/editing →
- Make artifacts reviewable inline in the Review Queue; paths alone are not enough.
- Add explicit gates before external effects: send, publish, schedule, commit/push/PR/merge, deploy, payment, credentials, destructive data changes.
- Record receipts: commands run, stdout/stderr/exit code, artifact paths, external handles, side-effect ledger.
- Add smoke tests that run without provider credentials by using
mock_outputwhere appropriate.
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.
- 12d ago First seen · 141 lines · 49 tokens per session scan A 4884c21fc966
hermes-workflows-creating is a skill published in the GitHub repository hugobowne/show-us-your-agent-skills (67 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 1,284 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 2026-08-30.
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