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 ailiheizi/workflow-to-skill --skill workflow-to-skill-with-surfacegit clone --depth 1 https://github.com/ailiheizi/workflow-to-skillWrote 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/ailiheizi/workflow-to-skill/workflow-to-skill-with-surface)<a href="https://agentmods.dev/skills/ailiheizi/workflow-to-skill/workflow-to-skill-with-surface"><img src="https://agentmods.dev/badge/skills/ailiheizi/workflow-to-skill/workflow-to-skill-with-surface/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/ailiheizi/workflow-to-skill/workflow-to-skill-with-surface"><img src="https://agentmods.dev/badge/skills/ailiheizi/workflow-to-skill/workflow-to-skill-with-surface.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00091 | $0.02529 |
| Opus 5 | $0.00046 | $0.01264 |
| Sonnet 5 | $0.00018 | $0.00506 |
| Haiku 4.5 | $0.00009 | $0.00253 |
Grade C, and why
workflow-to-skill-with-surface scanned grade C with 1 finding 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
- collect secrets or grant credentials, permissions, or authority; How it starts
The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workflow To Skill With Surface
Create one readable workflow Skill and, when supported, a dedicated Prompt Surface around it. The Skill is the single source of workflow method. The Surface only maps structured input to an ordinary Skill message and presents the Harness's ordinary result.
The target Harness loads the Skill, runs the Agent, and invokes existing CLI, MCP, HTTP, API, Dify, n8n, ComfyUI, or other capabilities. Do not create an executor, workflow runtime, Surface runtime, or second state protocol.
Authoring Method
Use one combined authoring and review flow:
- Clarify the workflow outcome, scope, inputs, outputs, side effects, completion criteria, target Harness, and representative success and failure cases. Confirm why a dedicated Surface is useful.
- Inspect real Harness documentation and capabilities. Confirm exact tool bindings, important parameter and result contracts, credential binding names, external workflow identity or version, lifecycle states, and success evidence. Confirm Skill installation and invocation plus the Harness's ordinary message, continuation, and result presentation APIs.
- Present one proposal covering the workflow and Surface together. Label user-confirmed choices, proposed safe defaults, and unresolved material decisions. Include the visible input-to-prompt mapping and Surface boundary.
- Ask for one review of the shared material decisions. Ask again only if a material choice remains unresolved or later changes; do not create a second approval round merely because Surface implementation follows Skill authoring.
- Write the candidate
SKILL.mdafter material choices are confirmed or covered by an explicit unattended policy. The Skill must remain complete and usable without the Surface. - Structurally validate, install, discover, and explicitly invoke the Skill through the Harness's ordinary path when authorized. Confirm the intended candidate was loaded rather than a stale or conflicting copy. Exercise safe success and material stop or failure cases before treating the Surface as ready.
- Implement the Surface only through the target Harness's native UI and ordinary message/result APIs. If those APIs are unavailable, report the adapter gap instead of adding a Workflow-to-Skill runtime.
- Validate input mapping, ordinary invocation-path parity, untrusted input, secrets, result projection, failure behavior, and review continuation when offered. Separate observed behavior from untested claims.
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 · 272 lines · 91 tokens per session scan C daed6a970d7a
workflow-to-skill-with-surface is a skill published in the GitHub repository ailiheizi/workflow-to-skill (2 stars, last pushed 18d ago), licensed Apache-2.0. It adds 91 tokens to every session and 2,529 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (harvests environment variables). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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