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 Cognigy/cognigy-plugin --skill flow-nodesgit clone --depth 1 https://github.com/Cognigy/cognigy-pluginWrote 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/cognigy/cognigy-plugin/flow-nodes)<a href="https://agentmods.dev/skills/cognigy/cognigy-plugin/flow-nodes"><img src="https://agentmods.dev/badge/skills/cognigy/cognigy-plugin/flow-nodes/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/cognigy/cognigy-plugin/flow-nodes"><img src="https://agentmods.dev/badge/skills/cognigy/cognigy-plugin/flow-nodes.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Data Exfiltration · line 286 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 304 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00068 | $0.06834 |
| Opus 5.5 | $0.00027 | $0.02734 |
| Sonnet 5.5 | $0.00014 | $0.01367 |
| Haiku 4.5 | $0.00007 | $0.00683 |
Grade A, and why
flow-nodes 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 14d 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 — 582 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Flow Node Reference
Use manage_flow_nodes to add logic nodes inside tool branches only. Nodes are helpers for tools — they must ALWAYS be created under a tool, never as standalone pre-agent nodes.
CRITICAL: NEVER add nodes before the AI Agent Job node. Pre-agent nodes cause conversation loops and break the agent's ability to orchestrate. ALL logic — including authentication, data collection, greetings, and conditional behavior — must be implemented as agent tools.
Voice exception — Set Session Config: The one node that should run before the AI Agent node is a setSessionConfig (Set Session Config) node, and only in voice flows. It applies per-session speech settings (barge-in, ASR, STT/TTS, input timeouts) and must be the first node. The audit_voice_agent tool checks for this and can create it by prepending before the AI Agent node. Do not add any other pre-agent nodes.
LLM Prompt exception: llmPrompt (llmPromptV2) is a top-level raw LLM node for flows with no AI Agent node. Create it only when the user asks for an LLM Prompt node by name; otherwise use the AI Agent default. Reading or updating existing llmPromptV2 nodes is fine. See the LLM Prompt section.
Quick Start (tool-first workflow)
1. Create a tool — create_tool { aiAgentId, toolType: 'tool', name: 'Process Order', config: { toolId: 'process_order', description: 'Process a customer order' } } → returns toolNodeId
2. Get the flowId — from create_ai_agent response, or list_resources { resourceType: 'flow', projectId }
3. Add a node inside the tool — manage_flow_nodes { operation: 'create', flowId, parentNodeId: '<toolNodeId>', mode: 'appendChild', nodeType: 'code', label: 'Validate Order', config: { code: '...' } }
4. Add more nodes — manage_flow_nodes { operation: 'create', flowId, parentNodeId: '<previousNodeId>', mode: 'append', nodeType: 'say', label: 'Confirm', config: { text: 'Order processed!' } }
5. List all nodes — manage_flow_nodes { operation: 'list', flowId } (id, type, label, parentId, isDisabled when true — no config)
Read one node with its config before editing — manage_flow_nodes { operation: 'get', flowId, nodeId: '<id>' }
6. Update a node — manage_flow_nodes { operation: 'update', flowId, nodeId: '<id>', config: { text: 'Updated!' } }
7. Delete a node — manage_flow_nodes { operation: 'delete', flowId, nodeId: '<id>' }
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.
- 14d ago Changed · +2 lines · +16 tokens per session f49aee61638e
- 25d ago Changed · +53 lines 54cb1b308339
- 1mo ago Changed · +70 lines e5b7daa3b774
- 2mo ago First seen · 457 lines · 52 tokens per session scan A 39f9480638b4
flow-nodes is a skill published in the GitHub repository Cognigy/cognigy-plugin (18 stars, last pushed yesterday), licensed MIT. It adds 68 tokens to every session and 6,834 once invoked, about $0.0003 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 2026-08-31.
flow-nodes compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| flow-nodesCognigy/cognigy-plugin | Skill | 18 | yesterday | MIT | A | 68 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |