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 cyberbird2048/gbrainmcp-clean --skill webhook-transformsgit clone --depth 1 https://github.com/cyberbird2048/gbrainmcp-cleanWrote 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/cyberbird2048/gbrainmcp-clean/webhook-transforms)<a href="https://agentmods.dev/skills/cyberbird2048/gbrainmcp-clean/webhook-transforms"><img src="https://agentmods.dev/badge/skills/cyberbird2048/gbrainmcp-clean/webhook-transforms.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 | $0.00046 | $0.00577 |
| Opus 5 | $0.00023 | $0.00289 |
| Sonnet 5 | $0.00009 | $0.00115 |
| Haiku 4.5 | $0.00005 | $0.00058 |
Grade A, and why
webhook-transforms 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 7d 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.
This is a copy
100% identical to webhook-transforms — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Webhook Transforms
Contract
This skill guarantees:
- External events are transformed into brain pages with proper citations
- Raw payloads are preserved (dead-letter queue if transform fails)
- Entity extraction runs on every transformed event
- Input sanitization: no raw HTML/script passes to brain pages
- Error handling: transform failure logs raw payload, retries once
Phases
-
Define transform. Map event schema to brain page format:
- Input: raw webhook payload (JSON)
- Output: brain page content (markdown) + metadata (slug, type, citations)
- Must sanitize: strip HTML tags, escape script content
-
Register webhook URL. Provide the external service with the webhook endpoint.
-
On event received:
- Parse payload
- Run transform function
- Write brain page via
gbrain put - Extract entities, run enrichment
- Add timeline entries to mentioned entities
- Sync:
gbrain sync
-
Error handling:
- If transform throws: log raw payload to
_dead-letter/{timestamp}.md - Surface error type to agent
- Retry once
- Don't lose events
- If transform throws: log raw payload to
Example Transforms
SMS Received
Input: {from: "+1555...", body: "Meeting moved to 3pm", timestamp: "..."}
Output: Timeline entry on sender's brain page + task update if action item detected
Meeting Completed
Input: {title: "Weekly sync", attendees: [...], transcript: "...", summary: "..."}
Output: Delegate to meeting-ingestion skill
Social Mention
Input: {platform: "twitter", author: "@handle", text: "...", url: "..."}
Output: Brain page in media/ + entity extraction + backlinks
Output Format
Event transformed and written to brain. Report: "Webhook: {event_type} from {source} → {brain_page_path}"
Anti-Patterns
- Passing raw HTML/script to brain pages (XSS risk)
- Silently dropping events when transform fails (use dead-letter queue)
- Processing webhooks without entity extraction
- Not sanitizing external input before brain writes
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.
- 7d ago First seen · 84 lines · 46 tokens per session scan A b774293297af
webhook-transforms is a skill published in the GitHub repository cyberbird2048/gbrainmcp-clean (0 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 577 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to webhook-transforms, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
media-ingest
Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain. Multi-format handling with entity extraction and backlink propagation. Covers video-ingest, youtube-ingest, and book-ingest subtypes.
mem0-oss-to-platform
Plan and then execute a migration of a project from the mem0 open-source / self-hosted SDK (the local Memory class) to the mem0 Platform / hosted / managed SDK (the MemoryClient class). Use this whenever a developer wants to move, switch, or migrate their mem0 usage off OSS/self-hosted to the hosted API — e.g.…
Cortex
Operate Cortex, the LifeOS memory system — the typed Knowledge Archive (People, Companies, Ideas, Research with typed related: links) plus recall of prior work sessions, ISAs, and conversations. Search, add, harvest, develop, ingest, distill, graph-navigate, recall. USE WHEN cortex, knowledge, knowledge base, search…
memory
Use when the user asks to remember, recall, forget, update, search, or inspect durable OpenSquilla memory, including profile facts in USER.md and long-term notes in MEMORY.md or memory//.md.
ha-data-stores
Map of Hope Agent's local data stores and safe read-only query workflow. Use when the user asks where Hope Agent stores data, wants to inspect sessions/messages/memory/logs/background jobs/knowledge indexes/settings, asks the model to query local app data, or debugging requires checking persisted state. Trigger…
establishing-project-context
Use when the user asks to establish shared project language, or project work exposes a conflicting, renamed, or deprecated domain term that needs active semantic modeling. Routine small tasks stay on the fast path.