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 agentmods add skills/wellapp-ai/well/bpmn-workflownpx skills add WellApp-ai/Well --skill bpmn-workflowgit clone --depth 1 https://github.com/WellApp-ai/WellWrote 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/wellapp-ai/well/bpmn-workflow)<a href="https://agentmods.dev/skills/wellapp-ai/well/bpmn-workflow"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/bpmn-workflow.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 | $0.00021 | $0.01402 |
| Opus 5 | $0.00010 | $0.00701 |
| Sonnet 5 | $0.00004 | $0.00280 |
| Haiku 4.5 | $0.00002 | $0.00140 |
Grade A, and why
bpmn-workflow 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 6d 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 — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BPMN Workflow Skill
Generate BPMN 2.0 process diagrams from feature specifications, link them to Gherkin scenarios, and compose a system-wide workflow diagram.
When to Use
- After completing Ask mode (feature exploration) to visualize the flow
- When documenting system processes for stakeholders
- Before Plan mode to ensure all scenarios are captured
- When updating existing features with new scenarios
Prerequisites
- Feature has been explored in Ask mode with wireframes
- User flows have been identified
- API endpoints (if any) have been specified
Instructions
Phase 1: Gather Feature Context
Step 1.1: Check for existing .feature files
Glob docs/bpmn/features/**/*.feature
If found, parse existing scenarios:
CallMcpTool:
server: "bpmn-mcp"
toolName: "read-feature"
arguments: { "featurePath": "docs/bpmn/features/{feature-id}/{feature-id}.feature" }
Step 1.2: If no .feature file exists, generate scenarios from:
- Ask mode wireframes (each screen = potential scenario)
- User flow descriptions
- API endpoints defined (CRUD operations = scenarios)
- Edge cases identified (error states, empty states)
Phase 2: Generate Gherkin (if needed)
If generating new scenarios, structure them as:
Feature: [Feature Name]
As a [user type]
I want to [action]
So that [benefit]
Scenario: [Happy path name]
Given [precondition]
When [action]
Then [expected result]
Scenario: [Error case name]
Given [precondition]
When [invalid action]
Then [error handling]
Scenario naming conventions:
- Happy path:
Successful [action],[Action] completes - Validation:
[Action] with invalid [field] - Error:
[Action] when [error condition] - Edge:
[Action] with [edge case]
Phase 3: Generate BPMN
Call the generate-bpmn MCP tool:
CallMcpTool:
server: "bpmn-mcp"
toolName: "generate-bpmn"
arguments: {
"featureId": "{feature-id}",
"featureName": "{Feature Name}",
"scenarios": [
{
"id": "{scenario-id}",
"name": "{Scenario Name}",
"steps": [
{ "keyword": "Given", "text": "{step text}" },
{ "keyword": "When", "text": "{step text}" },
{ "keyword": "Then", "text": "{step text}" }
]
}
],
"outputPath": "docs/bpmn/features/{feature-id}/{feature-id}.bpmn"
}
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.
- 6d ago First seen · 211 lines · 21 tokens per session scan A f637566a7dd5
bpmn-workflow is a skill published in the GitHub repository WellApp-ai/Well (340 stars, last pushed 29d ago), licensed MIT. It adds 21 tokens to every session and 1,402 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 2026-08-30.
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