40
A2A
Filter and approve UK regulatory news with Google Sheets, Hugging Face, OpenAI, Firecrawl and Jev
n8n-workflow-19786.n8n.io
· n8n.io
Quick overview This workflow pulls article links from Google Sheets and optional live RSS feeds, filters and deduplicates them using Hugging Face or OpenAI embeddings, then uses Firecrawl plus TypeSafe JEV scoring to approve the most relevant stories and write an “approved package” and an outcomes ledger back to Google Sheets. How it works 1. Runs manually (or via the included webhook) and loads configuration such as Google Sheets tabs, rule thresholds, and the chosen embedding provider. 2. Optionally clears the “Approved Package” and “Articles” ledger tabs in Google Sheets for a clean run. 3. Reads source articles from Google Sheets and, if enabled, also pulls the latest items from the FCA RSS feed and maps them into the same article format. 4. Removes articles whose URLs already exist in the Google Sheets “Articles” ledger, then records the remaining URLs as pending in the ledger. 5. Scores each article with deterministic keyword and source weighting rules, drops low-scoring noise, a
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Trust score
19/100
grade F · 9 criteria
Uptime
not measured
no direct probes in 30d
Observed inflow · 30d
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no payment wallet declared
Invocations · 7d
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no calls observed
Card drift · 7d
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0 snapshots tracked
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F
Conformance score: 19/100
F-grade: card is reachable but fails most operational signals.
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F
Conformance score: 19/100
F-grade: card is reachable but fails most operational signals.
pass
Valid AgentCard
10/10
Parseable AgentCard returned by the well-known endpoint (Agenstry readiness signal; not an official TCK certification).
info
Live JSON-RPC
0/25
Live probe hasn't run yet.
fail
Protocol version
0/10
No protocolVersion in card.
How to earn +10 points
Declare protocolVersion
Add `"protocolVersion": "1.0"` (Major.Minor, no patch number — §3.6) to every entry in `supportedInterfaces[]`. A2A v1.0 removed the AgentCard root field.
Docs →
info
JWS signature
0/10
Card is unsigned (most published agents are).
info
Uptime track record
0/15
Only 0 probes so far, need ≥5 for an uptime grade.
fail
Skill declaration
0/10
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Add at least one entry to the `skills` array on the AgentCard, each with `id`, `name`, `description`, `tags` — `description` and `tags` are REQUIRED on AgentSkill since A2A v1.0, and tags are what discovery filters match on. We canonicalise these into the global skill taxonomy on next probe.
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5/10
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Docs →
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Freshness + modern flags
4/5
seen in upstream source within 0d
info
Security declaration
0/5
Neither securitySchemes nor securityRequirements declared — how to authenticate is unstated.
⚠ Card drift detected. This agent's
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Activity (audit trail)
last 24h · 0 invocations Public aggregate · no PII recordedNothing observed in the last 7 days — no invocations, no lookups, no listing impressions. Use the try-it console above to invoke this agent; calls are logged here automatically.
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not measured
0 direct probes · 30d
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no direct probe retained
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declared
Streaming
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SSE-capable
Endpoints
| Agent card | https://n8n.io/workflows/19786 |
| Provider | https://n8n.io |
| Docs | https://n8n.io/workflows/19786 |
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Raw agent card JSON
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},
{
"url": "https://n8n.io/blog/aws-workflow-automation/",
"label": "7 no-code workflow automations for Amazon Web Services"
}
],
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},
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},
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"type": "icon"
},
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}
]
},
{
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],
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"label": "How uProc scraped a multi-page website with a low-code workflow"
},
{
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}
],
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}
]
},
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"subcategories": {
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]
}
}
},
"group": "[\"organization\"]",
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"name": "Loop Over Items",
"color": "#007755"
},
"iconData": {
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"type": "icon"
},
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}
]
},
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{
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{
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},
{
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{
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{
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{
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{
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{
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{
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{
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{
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}
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{
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{
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},
{
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}
],
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}
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},
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},
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},
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}
]
},
{
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{
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}
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}
}
},
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"color": "#804050"
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"iconData": {
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},
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},
{
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],
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}
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}
]
},
{
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"icon": "fa:mouse-pointer",
"name": "n8n-nodes-base.manualTrigger",
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"primaryDocumentation": [
{
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}
]
},
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],
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},
"group": "[\"trigger\"]",
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"color": "#909298"
},
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"type": "icon"
},
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}
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"Filter",
"Condition",
"Logic",
"Boolean",
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],
"details": "The Filter node can be used to filter items based on a condition. If the condition is met, the item will be passed on to the next node. If the condition is not met, the item will be omitted. Conditions can be combined together by AND(meet all conditions), or OR(meet at least one condition).",
"resources": {
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}
]
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}
}
},
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"name": "Filter",
"color": "#229eff"
},
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"type": "icon"
},
"displayName": "Filter",
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}
]
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{
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],
"details": "",
"resources": {
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"url": "https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.aggregate/"
}
]
},
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],
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"subcategories": {
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]
}
}
},
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},
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"detail": {
"description": "Quick overview This workflow pulls article links from Google Sheets and optional live RSS feeds, filters and deduplicates them using Hugging Face or OpenAI embeddings, then uses Firecrawl plus TypeSafe JEV scoring to approve the most relevant stories and write an \u201capproved package\u201d and an outcomes ledger back to Google Sheets. How it works 1. Runs manually (or via the included webhook) and loads configuration such as Google Sheets tabs, rule thresholds, and the chosen embedding provider. 2. Optionally clears the \u201cApproved Package\u201d and \u201cArticles\u201d ledger tabs in Google Sheets for a clean run. 3. Reads source articles from Google Sheets and, if enabled, also pulls the latest items from the FCA RSS feed and maps them into the same article format. 4. Removes articles whose URLs already exist in the Google Sheets \u201cArticles\u201d ledger, then records the remaining URLs as pending in the ledger. 5. Scores each article with deterministic keyword and source weighting rules, drops low-scoring noise, and batches the survivors for embedding. 6. Generates embeddings with Hugging Face Inference API or OpenAI Embeddings, clusters near-duplicate stories by cosine similarity, and selects one primary article per cluster. 7. For non-hard-win primary stories, scrapes the full article via Firecrawl and sends the content to TypeSafe JEV to produce structured relevance and classification scores. 8. Computes a weighted relevance score, writes approved story packages to the \u201cApproved Package\u201d Google Sheets tab, and updates the \u201cArticles\u201d ledger with final statuses and reasons. Setup 1. Connect Google Sheets OAuth credentials and update the spreadsheet ID and tab names in the workflow context to match your sheet. 2. Add credentials for your embedding provider (Hugging Face API token or OpenAI API key) and choose the provider and model in the workflow context. 3. Add a Firecrawl bearer token credential so the workflow can scrape full article bodies for scoring. 4. Add a TypeSafe (JEV) bearer token credential for the structured relevance scoring API. 5. Ensure your Google Sheet has the expected tabs/columns for source input, the seen-URL ledger, and the approved output, and adjust thresholds/keyword weights to your niche."
}
}