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Code Issues Projects Releases Packages Wiki Activity Actions 4

docs(website): dedicated page per bundled + optional skill (#14929)

Browse source 
Generates a full dedicated Docusaurus page for every one of the 132 skills
(73 bundled + 59 optional) under website/docs/user-guide/skills/{bundled,optional}/<category>/.
Each page carries the skill's description, metadata (version, author, license,
dependencies, platform gating, tags, related skills cross-linked to their own
pages), and the complete SKILL.md body that Hermes loads at runtime.

Previously the two catalog pages just listed skills with a one-line blurb and
no way to see what the skill actually did — users had to go read the source
repo. Now every skill has a browsable, searchable, cross-linked reference in
the docs.

- website/scripts/generate-skill-docs.py — generator that reads skills/ and
  optional-skills/, writes per-skill pages, regenerates both catalog indexes,
  and rewrites the Skills section of sidebars.ts. Handles MDX escaping
  (outside fenced code blocks: curly braces, unsafe HTML-ish tags) and
  rewrites relative references/*.md links to point at the GitHub source.
- website/docs/reference/skills-catalog.md — regenerated; each row links to
  the new dedicated page.
- website/docs/reference/optional-skills-catalog.md — same.
- website/sidebars.ts — Skills section now has Bundled / Optional subtrees
  with one nested category per skill folder.
- .github/workflows/{docs-site-checks,deploy-site}.yml — run the generator
  before docusaurus build so CI stays in sync with the source SKILL.md files.

Build verified locally with `npx docusaurus build`. Only remaining warnings
are pre-existing broken link/anchor issues in unrelated pages.
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---
title: "Canvas — Canvas LMS integration — fetch enrolled courses and assignments using API token authentication"
sidebar_label: "Canvas"
description: "Canvas LMS integration — fetch enrolled courses and assignments using API token authentication"
---
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
# Canvas
Canvas LMS integration — fetch enrolled courses and assignments using API token authentication.
## Skill metadata
| | |
|---|---|
| Source | Optional — install with `hermes skills install official/productivity/canvas` |
| Path | `optional-skills/productivity/canvas` |
| Version | `1.0.0` |
| Author | community |
| License | MIT |
| Tags | `Canvas`, `LMS`, `Education`, `Courses`, `Assignments` |
## Reference: full SKILL.md
:::info
The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
:::
# Canvas LMS — Course & Assignment Access
Read-only access to Canvas LMS for listing courses and assignments.
## Scripts
- `scripts/canvas_api.py` — Python CLI for Canvas API calls
## Setup
1. Log in to your Canvas instance in a browser
2. Go to **Account → Settings** (click your profile icon, then Settings)
3. Scroll to **Approved Integrations** and click **+ New Access Token**
4. Name the token (e.g., "Hermes Agent"), set an optional expiry, and click **Generate Token**
5. Copy the token and add to `~/.hermes/.env`:
```
CANVAS_API_TOKEN=your_token_here
CANVAS_BASE_URL=https://yourschool.instructure.com
```
The base URL is whatever appears in your browser when you're logged into Canvas (no trailing slash).
## Usage
```bash
CANVAS="python $HERMES_HOME/skills/productivity/canvas/scripts/canvas_api.py"
# List all active courses
$CANVAS list_courses --enrollment-state active
# List all courses (any state)
$CANVAS list_courses
# List assignments for a specific course
$CANVAS list_assignments 12345
# List assignments ordered by due date
$CANVAS list_assignments 12345 --order-by due_at
```
## Output Format
**list_courses** returns:
```json
[{"id": 12345, "name": "Intro to CS", "course_code": "CS101", "workflow_state": "available", "start_at": "...", "end_at": "..."}]
```
**list_assignments** returns:
```json
[{"id": 67890, "name": "Homework 1", "due_at": "2025-02-15T23:59:00Z", "points_possible": 100, "submission_types": ["online_upload"], "html_url": "...", "description": "...", "course_id": 12345}]
```
Note: Assignment descriptions are truncated to 500 characters. The `html_url` field links to the full assignment page in Canvas.
## API Reference (curl)
```bash
# List courses
curl -s -H "Authorization: Bearer $CANVAS_API_TOKEN" \
"$CANVAS_BASE_URL/api/v1/courses?enrollment_state=active&per_page=10"
# List assignments for a course
curl -s -H "Authorization: Bearer $CANVAS_API_TOKEN" \
"$CANVAS_BASE_URL/api/v1/courses/COURSE_ID/assignments?per_page=10&order_by=due_at"
```
Canvas uses `Link` headers for pagination. The Python script handles pagination automatically.
## Rules
- This skill is **read-only** — it only fetches data, never modifies courses or assignments
- On first use, verify auth by running `$CANVAS list_courses` — if it fails with 401, guide the user through setup
- Canvas rate-limits to ~700 requests per 10 minutes; check `X-Rate-Limit-Remaining` header if hitting limits
## Troubleshooting
| Problem | Fix |
|---------|-----|
| 401 Unauthorized | Token invalid or expired — regenerate in Canvas Settings |
| 403 Forbidden | Token lacks permission for this course |
| Empty course list | Try `--enrollment-state active` or omit the flag to see all states |
| Wrong institution | Verify `CANVAS_BASE_URL` matches the URL in your browser |
| Timeout errors | Check network connectivity to your Canvas instance |

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---
title: "Memento Flashcards — Spaced-repetition flashcard system"
sidebar_label: "Memento Flashcards"
description: "Spaced-repetition flashcard system"
---
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
# Memento Flashcards
Spaced-repetition flashcard system. Create cards from facts or text, chat with flashcards using free-text answers graded by the agent, generate quizzes from YouTube transcripts, review due cards with adaptive scheduling, and export/import decks as CSV.
## Skill metadata
| | |
|---|---|
| Source | Optional — install with `hermes skills install official/productivity/memento-flashcards` |
| Path | `optional-skills/productivity/memento-flashcards` |
| Version | `1.0.0` |
| Author | Memento AI |
| License | MIT |
| Platforms | macos, linux |
| Tags | `Education`, `Flashcards`, `Spaced Repetition`, `Learning`, `Quiz`, `YouTube` |
## Reference: full SKILL.md
:::info
The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
:::
# Memento Flashcards — Spaced-Repetition Flashcard Skill
## Overview
Memento gives you a local, file-based flashcard system with spaced-repetition scheduling.
Users can chat with their flashcards by answering in free text and having the agent grade the response before scheduling the next review.
Use it whenever the user wants to:
- **Remember a fact** — turn any statement into a Q/A flashcard
- **Study with spaced repetition** — review due cards with adaptive intervals and agent-graded free-text answers
- **Quiz from a YouTube video** — fetch a transcript and generate a 5-question quiz
- **Manage decks** — organise cards into collections, export/import CSV
All card data lives in a single JSON file. No external API keys are required — you (the agent) generate flashcard content and quiz questions directly.
User-facing response style for Memento Flashcards:
- Use plain text only. Do not use Markdown formatting in replies to the user.
- Keep review and quiz feedback brief and neutral. Avoid extra praise, pep, or long explanations.
## When to Use
Use this skill when the user wants to:
- Save facts as flashcards for later review
- Review due cards with spaced repetition
- Generate a quiz from a YouTube video transcript
- Import, export, inspect, or delete flashcard data
Do not use this skill for general Q&A, coding help, or non-memory tasks.
## Quick Reference
| User intent | Action |
|---|---|
| "Remember that X" / "save this as a flashcard" | Generate a Q/A card, call `memento_cards.py add` |
| Sends a fact without mentioning flashcards | Ask "Want me to save this as a Memento flashcard?" — only create if confirmed |
| "Create a flashcard" | Ask for Q, A, collection; call `memento_cards.py add` |
| "Review my cards" | Call `memento_cards.py due`, present cards one-by-one |
| "Quiz me on [YouTube URL]" | Call `youtube_quiz.py fetch VIDEO_ID`, generate 5 questions, call `memento_cards.py add-quiz` |
| "Export my cards" | Call `memento_cards.py export --output PATH` |
| "Import cards from CSV" | Call `memento_cards.py import --file PATH --collection NAME` |
| "Show my stats" | Call `memento_cards.py stats` |
| "Delete a card" | Call `memento_cards.py delete --id ID` |
| "Delete a collection" | Call `memento_cards.py delete-collection --collection NAME` |
## Card Storage
Cards are stored in a JSON file at:
```
~/.hermes/skills/productivity/memento-flashcards/data/cards.json
```
**Never edit this file directly.** Always use `memento_cards.py` subcommands. The script handles atomic writes (write to temp file, then rename) to prevent corruption.
The file is created automatically on first use.
## Procedure
### Creating Cards from Facts
### Activation Rules
Not every factual statement should become a flashcard. Use this three-tier check:
1. **Explicit intent** — the user mentions "memento", "flashcard", "remember this", "save this card", "add a card", or similar phrasing that clearly requests a flashcard → **create the card directly**, no confirmation needed.
2. **Implicit intent** — the user sends a factual statement without mentioning flashcards (e.g. "The speed of light is 299,792 km/s") → **ask first**: "Want me to save this as a Memento flashcard?" Only create the card if the user confirms.
3. **No intent** — the message is a coding task, a question, instructions, normal conversation, or anything that is clearly not a fact to memorize → **do NOT activate this skill at all**. Let other skills or default behavior handle it.
When activation is confirmed (tier 1 directly, tier 2 after confirmation), generate a flashcard:
**Step 1:** Turn the statement into a Q/A pair. Use this format internally:
```
Turn the factual statement into a front-back pair.
Return exactly two lines:
Q: <question text>
A: <answer text>
Statement: "{statement}"
```
Rules:
- The question should test recall of the key fact
- The answer should be concise and direct
**Step 2:** Call the script to store the card:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add \
--question "What year did World War 2 end?" \
--answer "1945" \
--collection "History"
```
If the user doesn't specify a collection, use `"General"` as the default.
The script outputs JSON confirming the created card.
### Manual Card Creation
When the user explicitly asks to create a flashcard, ask them for:
1. The question (front of card)
2. The answer (back of card)
3. The collection name (optional — default to `"General"`)
Then call `memento_cards.py add` as above.
### Reviewing Due Cards
When the user wants to review, fetch all due cards:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due
```
This returns a JSON array of cards where `next_review_at <= now`. If a collection filter is needed:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due --collection "History"
```
**Review flow (free-text grading):**
Here is an example of the EXACT interaction pattern you must follow. The user answers, you grade them, tell them the correct answer, then rate the card.
**Example interaction:**
> **Agent:** What year did the Berlin Wall fall?
>
> **User:** 1991
>
> **Agent:** Not quite. The Berlin Wall fell in 1989. Next review is tomorrow.
> *(agent calls: memento_cards.py rate --id ABC --rating hard --user-answer "1991")*
>
> Next question: Who was the first person to walk on the moon?
**The rules:**
1. Show only the question. Wait for the user to answer.
2. After receiving their answer, compare it to the expected answer and grade it:
- **correct** → user got the key fact right (even if worded differently)
- **partial** → right track but missing the core detail
- **incorrect** → wrong or off-topic
3. **You MUST tell the user the correct answer and how they did.** Keep it short and plain-text. Use this format:
- correct: "Correct. Answer: &#123;answer&#125;. Next review in 7 days."
- partial: "Close. Answer: &#123;answer&#125;. &#123;what they missed&#125;. Next review in 3 days."
- incorrect: "Not quite. Answer: &#123;answer&#125;. Next review tomorrow."
4. Then call the rate command: correct→easy, partial→good, incorrect→hard.
5. Then show the next question.
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py rate \
--id CARD_ID --rating easy --user-answer "what the user said"
```
**Never skip step 3.** The user must always see the correct answer and feedback before you move on.
If no cards are due, tell the user: "No cards due for review right now. Check back later!"
**Retire override:** At any point the user can say "retire this card" to permanently remove it from reviews. Use `--rating retire` for this.
### Spaced Repetition Algorithm
The rating determines the next review interval:
| Rating | Interval | ease_streak | Status change |
|---|---|---|---|
| **hard** | +1 day | reset to 0 | stays learning |
| **good** | +3 days | reset to 0 | stays learning |
| **easy** | +7 days | +1 | if ease_streak >= 3 → retired |
| **retire** | permanent | reset to 0 | → retired |
- **learning**: card is actively in rotation
- **retired**: card won't appear in reviews (user has mastered it or manually retired it)
- Three consecutive "easy" ratings automatically retire a card
### YouTube Quiz Generation
When the user sends a YouTube URL and wants a quiz:
**Step 1:** Extract the video ID from the URL (e.g. `dQw4w9WgXcQ` from `https://www.youtube.com/watch?v=dQw4w9WgXcQ`).
**Step 2:** Fetch the transcript:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/youtube_quiz.py fetch VIDEO_ID
```
This returns `{"title": "...", "transcript": "..."}` or an error.
If the script reports `missing_dependency`, tell the user to install it:
```bash
pip install youtube-transcript-api
```
**Step 3:** Generate 5 quiz questions from the transcript. Use these rules:
```
You are creating a 5-question quiz for a podcast episode.
Return ONLY a JSON array with exactly 5 objects.
Each object must contain keys 'question' and 'answer'.
Selection criteria:
- Prioritize important, surprising, or foundational facts.
- Skip filler, obvious details, and facts that require heavy context.
- Never return true/false questions.
- Never ask only for a date.
Question rules:
- Each question must test exactly one discrete fact.
- Use clear, unambiguous wording.
- Prefer What, Who, How many, Which.
- Avoid open-ended Describe or Explain prompts.
Answer rules:
- Each answer must be under 240 characters.
- Lead with the answer itself, not preamble.
- Add only minimal clarifying detail if needed.
```
Use the first 15,000 characters of the transcript as context. Generate the questions yourself (you are the LLM).
**Step 4:** Validate the output is valid JSON with exactly 5 items, each having non-empty `question` and `answer` strings. If validation fails, retry once.
**Step 5:** Store quiz cards:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add-quiz \
--video-id "VIDEO_ID" \
--questions '[{"question":"...","answer":"..."},...]' \
--collection "Quiz - Episode Title"
```
The script deduplicates by `video_id` — if cards for that video already exist, it skips creation and reports the existing cards.
**Step 6:** Present questions one-by-one using the same free-text grading flow:
1. Show "Question 1/5: ..." and wait for the user's answer. Never include the answer or any hint about revealing it.
2. Wait for the user to answer in their own words
3. Grade their answer using the grading prompt (see "Reviewing Due Cards" section)
4. **IMPORTANT: You MUST reply to the user with feedback before doing anything else.** Show the grade, the correct answer, and when the card is next due. Do NOT silently skip to the next question. Keep it short and plain-text. Example: "Not quite. Answer: &#123;answer&#125;. Next review tomorrow."
5. **After showing feedback**, call the rate command and then show the next question in the same message:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py rate \
--id CARD_ID --rating easy --user-answer "what the user said"
```
6. Repeat. Every answer MUST receive visible feedback before the next question.
### Export/Import CSV
**Export:**
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py export \
--output ~/flashcards.csv
```
Produces a 3-column CSV: `question,answer,collection` (no header row).
**Import:**
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py import \
--file ~/flashcards.csv \
--collection "Imported"
```
Reads a CSV with columns: question, answer, and optionally collection (column 3). If the collection column is missing, uses the `--collection` argument.
### Statistics
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py stats
```
Returns JSON with:
- `total`: total card count
- `learning`: cards in active rotation
- `retired`: mastered cards
- `due_now`: cards due for review right now
- `collections`: breakdown by collection name
## Pitfalls
- **Never edit `cards.json` directly** — always use the script subcommands to avoid corruption
- **Transcript failures** — some YouTube videos have no English transcript or have transcripts disabled; inform the user and suggest another video
- **Optional dependency** — `youtube_quiz.py` needs `youtube-transcript-api`; if missing, tell the user to run `pip install youtube-transcript-api`
- **Large imports** — CSV imports with thousands of rows work fine but the JSON output may be verbose; summarize the result for the user
- **Video ID extraction** — support both `youtube.com/watch?v=ID` and `youtu.be/ID` URL formats
## Verification
Verify the helper scripts directly:
```bash
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py stats
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py add --question "Capital of France?" --answer "Paris" --collection "General"
python3 ~/.hermes/skills/productivity/memento-flashcards/scripts/memento_cards.py due
```
If you are testing from the repo checkout, run:
```bash
pytest tests/skills/test_memento_cards.py tests/skills/test_youtube_quiz.py -q
```
Agent-level verification:
- Start a review and confirm feedback is plain text, brief, and always includes the correct answer before the next card
- Run a YouTube quiz flow and confirm each answer receives visible feedback before the next question

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---
title: "Siyuan"
sidebar_label: "Siyuan"
description: "SiYuan Note API for searching, reading, creating, and managing blocks and documents in a self-hosted knowledge base via curl"
---
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
# Siyuan
SiYuan Note API for searching, reading, creating, and managing blocks and documents in a self-hosted knowledge base via curl.
## Skill metadata
| | |
|---|---|
| Source | Optional — install with `hermes skills install official/productivity/siyuan` |
| Path | `optional-skills/productivity/siyuan` |
| Version | `1.0.0` |
| Author | FEUAZUR |
| License | MIT |
| Tags | `SiYuan`, `Notes`, `Knowledge Base`, `PKM`, `API` |
| Related skills | [`obsidian`](/docs/user-guide/skills/bundled/note-taking/note-taking-obsidian), [`notion`](/docs/user-guide/skills/bundled/productivity/productivity-notion) |
## Reference: full SKILL.md
:::info
The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
:::
# SiYuan Note API
Use the [SiYuan](https://github.com/siyuan-note/siyuan) kernel API via curl to search, read, create, update, and delete blocks and documents in a self-hosted knowledge base. No extra tools needed -- just curl and an API token.
## Prerequisites
1. Install and run SiYuan (desktop or Docker)
2. Get your API token: **Settings > About > API token**
3. Store it in `~/.hermes/.env`:
```
SIYUAN_TOKEN=your_token_here
SIYUAN_URL=http://127.0.0.1:6806
```
`SIYUAN_URL` defaults to `http://127.0.0.1:6806` if not set.
## API Basics
All SiYuan API calls are **POST with JSON body**. Every request follows this pattern:
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/..." \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"param": "value"}'
```
Responses are JSON with this structure:
```json
{"code": 0, "msg": "", "data": { ... }}
```
`code: 0` means success. Any other value is an error -- check `msg` for details.
**ID format:** SiYuan IDs look like `20210808180117-6v0mkxr` (14-digit timestamp + 7 alphanumeric chars).
## Quick Reference
| Operation | Endpoint |
|-----------|----------|
| Full-text search | `/api/search/fullTextSearchBlock` |
| SQL query | `/api/query/sql` |
| Read block | `/api/block/getBlockKramdown` |
| Read children | `/api/block/getChildBlocks` |
| Get path | `/api/filetree/getHPathByID` |
| Get attributes | `/api/attr/getBlockAttrs` |
| List notebooks | `/api/notebook/lsNotebooks` |
| List documents | `/api/filetree/listDocsByPath` |
| Create notebook | `/api/notebook/createNotebook` |
| Create document | `/api/filetree/createDocWithMd` |
| Append block | `/api/block/appendBlock` |
| Update block | `/api/block/updateBlock` |
| Rename document | `/api/filetree/renameDocByID` |
| Set attributes | `/api/attr/setBlockAttrs` |
| Delete block | `/api/block/deleteBlock` |
| Delete document | `/api/filetree/removeDocByID` |
| Export as Markdown | `/api/export/exportMdContent` |
## Common Operations
### Search (Full-Text)
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/search/fullTextSearchBlock" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"query": "meeting notes", "page": 0}' | jq '.data.blocks[:5]'
```
### Search (SQL)
Query the blocks database directly. Only SELECT statements are safe.
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/query/sql" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"stmt": "SELECT id, content, type, box FROM blocks WHERE content LIKE '\''%keyword%'\'' AND type='\''p'\'' LIMIT 20"}' | jq '.data'
```
Useful columns: `id`, `parent_id`, `root_id`, `box` (notebook ID), `path`, `content`, `type`, `subtype`, `created`, `updated`.
### Read Block Content
Returns block content in Kramdown (Markdown-like) format.
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/block/getBlockKramdown" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "20210808180117-6v0mkxr"}' | jq '.data.kramdown'
```
### Read Child Blocks
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/block/getChildBlocks" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "20210808180117-6v0mkxr"}' | jq '.data'
```
### Get Human-Readable Path
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/filetree/getHPathByID" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "20210808180117-6v0mkxr"}' | jq '.data'
```
### Get Block Attributes
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/attr/getBlockAttrs" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "20210808180117-6v0mkxr"}' | jq '.data'
```
### List Notebooks
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/notebook/lsNotebooks" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{}' | jq '.data.notebooks[] | {id, name, closed}'
```
### List Documents in a Notebook
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/filetree/listDocsByPath" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"notebook": "NOTEBOOK_ID", "path": "/"}' | jq '.data.files[] | {id, name}'
```
### Create a Document
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/filetree/createDocWithMd" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"notebook": "NOTEBOOK_ID",
"path": "/Meeting Notes/2026-03-22",
"markdown": "# Meeting Notes\n\n- Discussed project timeline\n- Assigned tasks"
}' | jq '.data'
```
### Create a Notebook
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/notebook/createNotebook" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"name": "My New Notebook"}' | jq '.data.notebook.id'
```
### Append Block to Document
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/block/appendBlock" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"parentID": "DOCUMENT_OR_BLOCK_ID",
"data": "New paragraph added at the end.",
"dataType": "markdown"
}' | jq '.data'
```
Also available: `/api/block/prependBlock` (same params, inserts at the beginning) and `/api/block/insertBlock` (uses `previousID` instead of `parentID` to insert after a specific block).
### Update Block Content
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/block/updateBlock" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"id": "BLOCK_ID",
"data": "Updated content here.",
"dataType": "markdown"
}' | jq '.data'
```
### Rename a Document
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/filetree/renameDocByID" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "DOCUMENT_ID", "title": "New Title"}'
```
### Set Block Attributes
Custom attributes must be prefixed with `custom-`:
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/attr/setBlockAttrs" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"id": "BLOCK_ID",
"attrs": {
"custom-status": "reviewed",
"custom-priority": "high"
}
}'
```
### Delete a Block
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/block/deleteBlock" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "BLOCK_ID"}'
```
To delete a whole document: use `/api/filetree/removeDocByID` with `{"id": "DOC_ID"}`.
To delete a notebook: use `/api/notebook/removeNotebook` with `{"notebook": "NOTEBOOK_ID"}`.
### Export Document as Markdown
```bash
curl -s -X POST "${SIYUAN_URL:-http://127.0.0.1:6806}/api/export/exportMdContent" \
-H "Authorization: Token $SIYUAN_TOKEN" \
-H "Content-Type: application/json" \
-d '{"id": "DOCUMENT_ID"}' | jq -r '.data.content'
```
## Block Types
Common `type` values in SQL queries:
| Type | Description |
|------|-------------|
| `d` | Document (root block) |
| `p` | Paragraph |
| `h` | Heading |
| `l` | List |
| `i` | List item |
| `c` | Code block |
| `m` | Math block |
| `t` | Table |
| `b` | Blockquote |
| `s` | Super block |
| `html` | HTML block |
## Pitfalls
- **All endpoints are POST** -- even read-only operations. Do not use GET.
- **SQL safety**: only use SELECT queries. INSERT/UPDATE/DELETE/DROP are dangerous and should never be sent.
- **ID validation**: IDs match the pattern `YYYYMMDDHHmmss-xxxxxxx`. Reject anything else.
- **Error responses**: always check `code != 0` in responses before processing `data`.
- **Large documents**: block content and export results can be very large. Use `LIMIT` in SQL and pipe through `jq` to extract only what you need.
- **Notebook IDs**: when working with a specific notebook, get its ID first via `lsNotebooks`.
## Alternative: MCP Server
If you prefer a native integration instead of curl, install the SiYuan MCP server:
```yaml
# In ~/.hermes/config.yaml under mcp_servers:
mcp_servers:
siyuan:
command: npx
args: ["-y", "@porkll/siyuan-mcp"]
env:
SIYUAN_TOKEN: "your_token"
SIYUAN_URL: "http://127.0.0.1:6806"
```

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@ -0,0 +1,434 @@
---
title: "Telephony — Give Hermes phone capabilities without core tool changes"
sidebar_label: "Telephony"
description: "Give Hermes phone capabilities without core tool changes"
---
{/* This page is auto-generated from the skill's SKILL.md by website/scripts/generate-skill-docs.py. Edit the source SKILL.md, not this page. */}
# Telephony
Give Hermes phone capabilities without core tool changes. Provision and persist a Twilio number, send and receive SMS/MMS, make direct calls, and place AI-driven outbound calls through Bland.ai or Vapi.
## Skill metadata
| | |
|---|---|
| Source | Optional — install with `hermes skills install official/productivity/telephony` |
| Path | `optional-skills/productivity/telephony` |
| Version | `1.0.0` |
| Author | Nous Research |
| License | MIT |
| Tags | `telephony`, `phone`, `sms`, `mms`, `voice`, `twilio`, `bland.ai`, `vapi`, `calling`, `texting` |
| Related skills | [`maps`](/docs/user-guide/skills/bundled/productivity/productivity-maps), [`google-workspace`](/docs/user-guide/skills/bundled/productivity/productivity-google-workspace), [`agentmail`](/docs/user-guide/skills/optional/email/email-agentmail) |
## Reference: full SKILL.md
:::info
The following is the complete skill definition that Hermes loads when this skill is triggered. This is what the agent sees as instructions when the skill is active.
:::
# Telephony — Numbers, Calls, and Texts without Core Tool Changes
This optional skill gives Hermes practical phone capabilities while keeping telephony out of the core tool list.
It ships with a helper script, `scripts/telephony.py`, that can:
- save provider credentials into `~/.hermes/.env`
- search for and buy a Twilio phone number
- remember that owned number for later sessions
- send SMS / MMS from the owned number
- poll inbound SMS for that number with no webhook server required
- make direct Twilio calls using TwiML `<Say>` or `<Play>`
- import the owned Twilio number into Vapi
- place outbound AI calls through Bland.ai or Vapi
## What this solves
This skill is meant to cover the practical phone tasks users actually want:
- outbound calls
- texting
- owning a reusable agent number
- checking messages that arrive to that number later
- preserving that number and related IDs between sessions
- future-friendly telephony identity for inbound SMS polling and other automations
It does **not** turn Hermes into a real-time inbound phone gateway. Inbound SMS is handled by polling the Twilio REST API. That is enough for many workflows, including notifications and some one-time-code retrieval, without adding core webhook infrastructure.
## Safety rules — mandatory
1. Always confirm before placing a call or sending a text.
2. Never dial emergency numbers.
3. Never use telephony for harassment, spam, impersonation, or anything illegal.
4. Treat third-party phone numbers as sensitive operational data:
- do not save them to Hermes memory
- do not include them in skill docs, summaries, or follow-up notes unless the user explicitly wants that
5. It is fine to persist the **agent-owned Twilio number** because that is part of the user's configuration.
6. VoIP numbers are **not guaranteed** to work for all third-party 2FA flows. Use with caution and set user expectations clearly.
## Decision tree — which service to use?
Use this logic instead of hardcoded provider routing:
### 1) "I want Hermes to own a real phone number"
Use **Twilio**.
Why:
- easiest path to buying and keeping a number
- best SMS / MMS support
- simplest inbound SMS polling story
- cleanest future path to inbound webhooks or call handling
Use cases:
- receive texts later
- send deployment alerts / cron notifications
- maintain a reusable phone identity for the agent
- experiment with phone-based auth flows later
### 2) "I only need the easiest outbound AI phone call right now"
Use **Bland.ai**.
Why:
- quickest setup
- one API key
- no need to first buy/import a number yourself
Tradeoff:
- less flexible
- voice quality is decent, but not the best
### 3) "I want the best conversational AI voice quality"
Use **Twilio + Vapi**.
Why:
- Twilio gives you the owned number
- Vapi gives you better conversational AI call quality and more voice/model flexibility
Recommended flow:
1. Buy/save a Twilio number
2. Import it into Vapi
3. Save the returned `VAPI_PHONE_NUMBER_ID`
4. Use `ai-call --provider vapi`
### 4) "I want to call with a custom prerecorded voice message"
Use **Twilio direct call** with a public audio URL.
Why:
- easiest way to play a custom MP3
- pairs well with Hermes `text_to_speech` plus a public file host or tunnel
## Files and persistent state
The skill persists telephony state in two places:
### `~/.hermes/.env`
Used for long-lived provider credentials and owned-number IDs, for example:
- `TWILIO_ACCOUNT_SID`
- `TWILIO_AUTH_TOKEN`
- `TWILIO_PHONE_NUMBER`
- `TWILIO_PHONE_NUMBER_SID`
- `BLAND_API_KEY`
- `VAPI_API_KEY`
- `VAPI_PHONE_NUMBER_ID`
- `PHONE_PROVIDER` (AI call provider: bland or vapi)
### `~/.hermes/telephony_state.json`
Used for skill-only state that should survive across sessions, for example:
- remembered default Twilio number / SID
- remembered Vapi phone number ID
- last inbound message SID/date for inbox polling checkpoints
This means:
- the next time the skill is loaded, `diagnose` can tell you what number is already configured
- `twilio-inbox --since-last --mark-seen` can continue from the previous checkpoint
## Locate the helper script
After installing this skill, locate the script like this:
```bash
SCRIPT="$(find ~/.hermes/skills -path '*/telephony/scripts/telephony.py' -print -quit)"
```
If `SCRIPT` is empty, the skill is not installed yet.
## Install
This is an official optional skill, so install it from the Skills Hub:
```bash
hermes skills search telephony
hermes skills install official/productivity/telephony
```
## Provider setup
### Twilio — owned number, SMS/MMS, direct calls, inbound SMS polling
Sign up at:
- https://www.twilio.com/try-twilio
Then save credentials into Hermes:
```bash
python3 "$SCRIPT" save-twilio ACXXXXXXXXXXXXXXXXXXXXXXXXXXXX your_auth_token_here
```
Search for available numbers:
```bash
python3 "$SCRIPT" twilio-search --country US --area-code 702 --limit 5
```
Buy and remember a number:
```bash
python3 "$SCRIPT" twilio-buy "+17025551234" --save-env
```
List owned numbers:
```bash
python3 "$SCRIPT" twilio-owned
```
Set one of them as the default later:
```bash
python3 "$SCRIPT" twilio-set-default "+17025551234" --save-env
# or
python3 "$SCRIPT" twilio-set-default PNXXXXXXXXXXXXXXXXXXXXXXXXXXXX --save-env
```
### Bland.ai — easiest outbound AI calling
Sign up at:
- https://app.bland.ai
Save config:
```bash
python3 "$SCRIPT" save-bland your_bland_api_key --voice mason
```
### Vapi — better conversational voice quality
Sign up at:
- https://dashboard.vapi.ai
Save the API key first:
```bash
python3 "$SCRIPT" save-vapi your_vapi_api_key
```
Import your owned Twilio number into Vapi and persist the returned phone number ID:
```bash
python3 "$SCRIPT" vapi-import-twilio --save-env
```
If you already know the Vapi phone number ID, save it directly:
```bash
python3 "$SCRIPT" save-vapi your_vapi_api_key --phone-number-id vapi_phone_number_id_here
```
## Diagnose current state
At any time, inspect what the skill already knows:
```bash
python3 "$SCRIPT" diagnose
```
Use this first when resuming work in a later session.
## Common workflows
### A. Buy an agent number and keep using it later
1. Save Twilio credentials:
```bash
python3 "$SCRIPT" save-twilio AC... auth_token_here
```
2. Search for a number:
```bash
python3 "$SCRIPT" twilio-search --country US --area-code 702 --limit 10
```
3. Buy it and save it into `~/.hermes/.env` + state:
```bash
python3 "$SCRIPT" twilio-buy "+17025551234" --save-env
```
4. Next session, run:
```bash
python3 "$SCRIPT" diagnose
```
This shows the remembered default number and inbox checkpoint state.
### B. Send a text from the agent number
```bash
python3 "$SCRIPT" twilio-send-sms "+15551230000" "Your deployment completed successfully."
```
With media:
```bash
python3 "$SCRIPT" twilio-send-sms "+15551230000" "Here is the chart." --media-url "https://example.com/chart.png"
```
### C. Check inbound texts later with no webhook server
Poll the inbox for the default Twilio number:
```bash
python3 "$SCRIPT" twilio-inbox --limit 20
```
Only show messages that arrived after the last checkpoint, and advance the checkpoint when you're done reading:
```bash
python3 "$SCRIPT" twilio-inbox --since-last --mark-seen
```
This is the main answer to “how do I access messages the number receives next time the skill is loaded?”
### D. Make a direct Twilio call with built-in TTS
```bash
python3 "$SCRIPT" twilio-call "+15551230000" --message "Hello! This is Hermes calling with your status update." --voice Polly.Joanna
```
### E. Call with a prerecorded / custom voice message
This is the main path for reusing Hermes's existing `text_to_speech` support.
Use this when:
- you want the call to use Hermes's configured TTS voice rather than Twilio `<Say>`
- you want a one-way voice delivery (briefing, alert, joke, reminder, status update)
- you do **not** need a live conversational phone call
Generate or host audio separately, then:
```bash
python3 "$SCRIPT" twilio-call "+155****0000" --audio-url "https://example.com/briefing.mp3"
```
Recommended Hermes TTS -> Twilio Play workflow:
1. Generate the audio with Hermes `text_to_speech`.
2. Make the resulting MP3 publicly reachable.
3. Place the Twilio call with `--audio-url`.
Example agent flow:
- Ask Hermes to create the message audio with `text_to_speech`
- If needed, expose the file with a temporary static host / tunnel / object storage URL
- Use `twilio-call --audio-url ...` to deliver it by phone
Good hosting options for the MP3:
- a temporary public object/storage URL
- a short-lived tunnel to a local static file server
- any existing HTTPS URL the phone provider can fetch directly
Important note:
- Hermes TTS is great for prerecorded outbound messages
- Bland/Vapi are better for **live conversational AI calls** because they handle the real-time telephony audio stack themselves
- Hermes STT/TTS alone is not being used here as a full duplex phone conversation engine; that would require a much heavier streaming/webhook integration than this skill is trying to introduce
### F. Navigate a phone tree / IVR with Twilio direct calling
If you need to press digits after the call connects, use `--send-digits`.
Twilio interprets `w` as a short wait.
```bash
python3 "$SCRIPT" twilio-call "+18005551234" --message "Connecting to billing now." --send-digits "ww1w2w3"
```
This is useful for reaching a specific menu branch before handing off to a human or delivering a short status message.
### G. Outbound AI phone call with Bland.ai
```bash
python3 "$SCRIPT" ai-call "+15551230000" "Call the dental office, ask for a cleaning appointment on Tuesday afternoon, and if they do not have Tuesday availability, ask for Wednesday or Thursday instead." --provider bland --voice mason --max-duration 3
```
Check status:
```bash
python3 "$SCRIPT" ai-status <call_id> --provider bland
```
Ask Bland analysis questions after completion:
```bash
python3 "$SCRIPT" ai-status <call_id> --provider bland --analyze "Was the appointment confirmed?,What date and time?,Any special instructions?"
```
### H. Outbound AI phone call with Vapi on your owned number
1. Import your Twilio number into Vapi:
```bash
python3 "$SCRIPT" vapi-import-twilio --save-env
```
2. Place the call:
```bash
python3 "$SCRIPT" ai-call "+15551230000" "You are calling to make a dinner reservation for two at 7:30 PM. If that is unavailable, ask for the nearest time between 6:30 and 8:30 PM." --provider vapi --max-duration 4
```
3. Check result:
```bash
python3 "$SCRIPT" ai-status <call_id> --provider vapi
```
## Suggested agent procedure
When the user asks for a call or text:
1. Determine which path fits the request via the decision tree.
2. Run `diagnose` if configuration state is unclear.
3. Gather the full task details.
4. Confirm with the user before dialing or texting.
5. Use the correct command.
6. Poll for results if needed.
7. Summarize the outcome without persisting third-party numbers to Hermes memory.
## What this skill still does not do
- real-time inbound call answering
- webhook-based live SMS push into the agent loop
- guaranteed support for arbitrary third-party 2FA providers
Those would require more infrastructure than a pure optional skill.
## Pitfalls
- Twilio trial accounts and regional rules can restrict who you can call/text.
- Some services reject VoIP numbers for 2FA.
- `twilio-inbox` polls the REST API; it is not instant push delivery.
- Vapi outbound calling still depends on having a valid imported number.
- Bland is easiest, but not always the best-sounding.
- Do not store arbitrary third-party phone numbers in Hermes memory.
## Verification checklist
After setup, you should be able to do all of the following with just this skill:
1. `diagnose` shows provider readiness and remembered state
2. search and buy a Twilio number
3. persist that number to `~/.hermes/.env`
4. send an SMS from the owned number
5. poll inbound texts for the owned number later
6. place a direct Twilio call
7. place an AI call via Bland or Vapi
## References
- Twilio phone numbers: https://www.twilio.com/docs/phone-numbers/api
- Twilio messaging: https://www.twilio.com/docs/messaging/api/message-resource
- Twilio voice: https://www.twilio.com/docs/voice/api/call-resource
- Vapi docs: https://docs.vapi.ai/
- Bland.ai: https://app.bland.ai/