Pinboard Manager

Interactive Pinboard bookmark management with tag auditing, dead link detection, and content timeliness checking.

Prerequisites

Tool	Type	Required	How to get
Pinboard account	service	Yes	pinboard.in
`PINBOARD_AUTH_TOKEN`	env var	Yes	See user-config.md
`curl`	cli	Yes	Built-in on macOS/Linux

Do NOT proactively verify these tools on skill load. If a command fails due to a missing tool or token, directly guide the user through setup step by step.

First-Time Setup

If references/tag-convention.md does not exist in the skill directory, run the Tag Convention Generator before any other mode:

Fetch all bookmarks via the Pinboard API
Analyze existing tags: frequency, patterns, languages, potential typos
Present findings to the user:
- Top 30 tags by frequency
- Tags that look like typos or duplicates
- Chinese/non-English tags that may need English equivalents
- Tags with inconsistent casing or separators
Ask the user about their preferred categories (tech, life, culture, etc.)
Generate references/tag-convention.md based on the analysis and user input, following the structure in references/tag-convention.example.md
Confirm with the user before saving

An example convention is provided at references/tag-convention.example.md for reference. Users should customize it to match their own bookmarking habits.

Mode Selection

User Intent	Mode	Section
「pinboard 整理 tag」「pinboard audit」「整理书签」	Tag Audit	Tag Audit Mode
「pinboard 检查死链」「pinboard check links」	Dead Link Detection	Dead Link Detection Mode
「pinboard 检查时效」「pinboard timeliness check」「pinboard 过时检测」	Timeliness Check	Timeliness Check Mode

API Helpers

All Pinboard API calls use these patterns:

Fetch bookmarks

# Fetch all bookmarks
curl -s "https://api.pinboard.in/v1/posts/all?auth_token=$PINBOARD_AUTH_TOKEN&format=json"

# Fetch bookmarks with toread=yes
curl -s "https://api.pinboard.in/v1/posts/all?auth_token=$PINBOARD_AUTH_TOKEN&format=json&toread=yes"

# Fetch a specific bookmark by URL
curl -s "https://api.pinboard.in/v1/posts/get?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL"

Update a bookmark (overwrite mode)

CRITICAL: Always pass ALL fields to avoid data loss. The /posts/add endpoint overwrites the entire bookmark.

curl -s "https://api.pinboard.in/v1/posts/add?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL&description=ENCODED_TITLE&extended=ENCODED_NOTES&tags=ENCODED_TAGS&shared=ORIGINAL_SHARED&toread=ORIGINAL_TOREAD&replace=yes"

Required fields to preserve:

url — the bookmark URL (identifier)
description — title
extended — notes/description
tags — space-separated tag list
shared — yes or no
toread — yes or no
replace — MUST be yes to update existing

Delete a bookmark

curl -s "https://api.pinboard.in/v1/posts/delete?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL"

Rate limiting

Pinboard recommends at most 1 API call per 3 seconds. When making multiple calls (batch updates, link checks), add sleep 3 between calls.

posts/all special limit: This endpoint is rate-limited to once every 5 minutes. Cache the result in /tmp/pinboard_all.json and reuse it within the same session. If both Tag Audit and Dead Link Detection are run consecutively, reuse the cached file.

Tag Audit Mode

Overview

Audit all bookmarks against the tag convention, present issues in batches, and apply fixes with user confirmation.

Reference: tag-convention.md (generated during first-time setup)

Step 1: Fetch all bookmarks

curl -s "https://api.pinboard.in/v1/posts/all?auth_token=$PINBOARD_AUTH_TOKEN&format=json" > /tmp/pinboard_all.json

Parse the JSON and count total bookmarks.

Step 2: Analyze tag issues

Load the tag convention from tag-convention.md and scan all bookmarks. Categorize issues:

Priority	Category	Example
1	Typos	`ainme` → `anime`
2	Missing tags	Bookmarks with empty `tags` field
3	Case issues	`Health` → `health`
4	Chinese tags	`终极文档` → `reference`
5	Concept overlap	`ai` + `llm` on same bookmark
6	Deprecated tags	`TODO`, year tags like `2025`

Step 3: Present issues in batches

For each category (in priority order), present 5-10 bookmarks per batch:

### Batch 1: Typos (3 items)

1. 「Some anime article」
   URL: https://example.com/anime
   Current tags: `ainme game`
   Suggested: `anime game`

2. 「Editor comparison」
   URL: https://example.com/editor
   Current tags: `editer tool`
   Suggested: `programming tool`

3. ...

Options: [confirm all] [modify] [skip all] [skip individual]

Step 4: Apply confirmed changes

For each confirmed change, update via /posts/add with replace=yes:

# URL-encode all parameters
curl -s "https://api.pinboard.in/v1/posts/add?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL&description=ENCODED_TITLE&extended=ENCODED_NOTES&tags=NEW_TAGS&shared=ORIGINAL_SHARED&toread=ORIGINAL_TOREAD&replace=yes"
sleep 3  # Rate limit

IMPORTANT: Preserve ALL original fields. Only modify tags.

Step 5: Summary

After all batches are processed, show:

Tag Audit Complete
- Bookmarks scanned: 200
- Issues found: 45
- Fixed: 38
- Skipped: 7

Dead Link Detection Mode

Overview

Check all bookmarks for broken URLs and report results for user action.

Step 1: Fetch all bookmarks

Same as Tag Audit Step 1.

Step 2: Check links in batches

Process 10 URLs per batch using HTTP HEAD requests:

# HEAD request with 10 second timeout
HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -L --max-redirs 5 -I -m 10 "URL")

Classification (based on final status after following redirects):

Status	Meaning	Action
2xx	Working	No action
403, 405	HEAD rejected	Retry with GET
4xx (other)	Broken	Report to user
5xx	Server error	Report to user
000	Timeout/unreachable	Report to user

For HEAD-rejected URLs, retry once with GET:

HTTP_STATUS=$(curl -s -o /dev/null -w "%{http_code}" -L --max-redirs 5 -m 10 "URL")

Step 3: Present results

Show broken links grouped by status:

### Dead Links Found (12 items)

#### 404 Not Found (5)
1. 「Article title」 — https://example.com/gone
   Tags: programming
   → [delete] [keep] [skip]

2. ...

#### Timeout (4)
1. 「Slow site article」 — https://slow-site.com/article
   Tags: reference
   → [delete] [keep] [skip]

#### Server Error 5xx (3)
1. ...

Step 4: Apply user decisions

For deletions:

curl -s "https://api.pinboard.in/v1/posts/delete?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL"
sleep 3  # Rate limit

Step 5: Summary

Dead Link Check Complete
- Links checked: 200
- Working: 188
- Broken: 8 (deleted: 5, kept: 3)
- Timeout: 4 (deleted: 1, kept: 3)

Timeliness Check Mode

Overview

Identify tech bookmarks whose content may be outdated using a two-stage approach: heuristic pre-filtering to narrow candidates, then AI content analysis via Jina Reader + current Claude session.

This mode does NOT auto-delete anything — all actions require user confirmation.

Step 1: Fetch all bookmarks

Reuse the cached file if available from a previous mode in this session:

# Only fetch if cache doesn't exist or is stale
if [ ! -f /tmp/pinboard_all.json ]; then
  curl -s "https://api.pinboard.in/v1/posts/all?auth_token=$PINBOARD_AUTH_TOKEN&format=json" > /tmp/pinboard_all.json
fi

Parse the JSON and count total bookmarks.

Step 2: Heuristic pre-filtering

Apply three filters in order to identify candidates for AI analysis:

Filter 1: Tag filter (tech only)

Include bookmarks with ANY of these tech-related tags:

llm, programming, python, javascript, typescript, web, devops, cloudflare, shell, github, database, security, home_assistant, iot, zigbee

Exclude bookmarks with ANY of these meta tags (even if they have tech tags):

evergreen, reference, collection

Filter 2: Age filter

Include bookmarks saved more than 2 years ago (based on the Pinboard time field).

Filter 3: Version detection

Include bookmarks whose title or URL contains version number patterns, regardless of age:

Named versions: React 16, Python 3.8, Vue 2, Angular 1.x
Version prefixes: v2.0, v1.x, v3
ECMAScript versions: ES5, ES6, ES2015
Framework-specific: Rails 4, Django 1.x, Node 12

Candidate condition

A bookmark is a candidate if it matches: Filter 1 AND (Filter 2 OR Filter 3)

Report the number of candidates found before proceeding:

Heuristic pre-filtering complete:
- Total bookmarks: 376
- Tech bookmarks (after tag filter): 120
- Candidates (age > 2y OR version detected): 35

Step 3: Content fetching via Jina Reader

For each candidate, fetch content using Jina Reader:

CONTENT=$(curl -s "https://r.jina.ai/BOOKMARK_URL" | head -c 5000)
sleep 2  # Rate limiting between requests

Error handling:

If Jina Reader returns an error or empty response → mark as "unable to fetch", skip this bookmark
If the URL is unreachable → skip and continue with next candidate
Always wait 2 seconds between Jina Reader requests

Step 4: AI timeliness analysis

For each successfully fetched candidate, analyze the content and determine timeliness. Output for each:

Field	Values	Description
Status	`outdated` / `possibly_outdated` / `still_valid`	Timeliness assessment
Reason	Free text	One sentence explaining the assessment
Suggestion	`delete` / `mark_evergreen` / `keep`	Recommended action

Assessment guidelines:

outdated: Content discusses deprecated APIs, removed features, old framework versions with no relevance today, or superseded best practices. Suggest delete.
possibly_outdated: Content references specific versions but core concepts may still apply, or the technology has evolved significantly. Suggest keep.
still_valid: Content discusses timeless concepts, patterns, or approaches that remain current. Suggest mark_evergreen.

Step 5: Batch presentation

Present results in batches of 5 candidates:

### Batch 1: Timeliness Analysis (5 items)

1. 「Introduction to React 16 Lifecycle Methods」
   URL: https://example.com/react-16-lifecycle
   Tags: javascript web
   Status: 🔴 outdated
   Reason: Article covers React 16 class component lifecycle methods; React 18+ recommends functional components with hooks
   Suggestion: delete

2. 「Understanding Python Type Hints」
   URL: https://example.com/python-types
   Tags: python programming
   Status: 🟢 still_valid
   Reason: Python type hints syntax and concepts remain current in Python 3.12+
   Suggestion: mark_evergreen

3. 「Setting up Webpack 3 for React」
   URL: https://example.com/webpack-3
   Tags: javascript web
   Status: 🔴 outdated
   Reason: Webpack 3 is deprecated; most projects use Webpack 5 or Vite
   Suggestion: delete

4. 「Git Branching Strategies」
   URL: https://example.com/git-branching
   Tags: programming github
   Status: 🟢 still_valid
   Reason: Git branching concepts are fundamental and haven't changed
   Suggestion: mark_evergreen

5. 「Django 1.11 Migration Guide」
   URL: https://example.com/django-1.11
   Tags: python web
   Status: 🟡 possibly_outdated
   Reason: Django 1.11 is EOL but some migration concepts may apply to newer versions
   Suggestion: keep

Options: [confirm suggestions] [modify individual] [skip all]

Use the AskUserQuestion tool to let the user choose their action for each batch.

Step 6: Apply user actions

For each bookmark based on user decision:

Delete (for outdated bookmarks user confirms):

curl -s "https://api.pinboard.in/v1/posts/delete?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL"
sleep 3  # Rate limit

Mark evergreen (for still_valid bookmarks user confirms):

# Add 'evergreen' to existing tags, preserve ALL other fields
curl -s "https://api.pinboard.in/v1/posts/add?auth_token=$PINBOARD_AUTH_TOKEN&format=json&url=ENCODED_URL&description=ENCODED_TITLE&extended=ENCODED_NOTES&tags=EXISTING_TAGS%20evergreen&shared=ORIGINAL_SHARED&toread=ORIGINAL_TOREAD&replace=yes"
sleep 3  # Rate limit

CRITICAL: When adding evergreen tag, preserve ALL original fields (description, extended, shared, toread). Only append evergreen to the tags list.

Skip: No API call, move to next item.

Step 7: Summary

After all batches are processed:

Timeliness Check Complete
- Total bookmarks: 376
- Candidates (after heuristic filter): 35
- Unable to fetch: 3
- Analyzed: 32
  - Outdated: 12 (deleted: 10, kept: 2)
  - Possibly outdated: 8 (all kept)
  - Still valid: 12 (marked evergreen: 10, kept: 2)
- Skipped: 5

Common Errors

Error	Cause	Fix
`PINBOARD_AUTH_TOKEN not set`	Env var missing	See user-config.md
`403 Forbidden` on API calls	Invalid or expired token	Re-check token at Pinboard settings
`429 Too Many Requests`	Rate limit exceeded	Increase sleep between calls; `posts/all` is limited to once per 5 min
Partial update lost data	Missing fields in `/posts/add`	Always pass ALL original fields with `replace=yes`
Jina Reader empty response	Site blocks Jina Reader or URL is broken	Skip this bookmark, mark as "unable to fetch"
Jina Reader timeout	Slow site or network issue	Skip and continue with next candidate

pinboard-manager

Pinboard Manager

Prerequisites

First-Time Setup

Mode Selection

API Helpers

Fetch bookmarks

Update a bookmark (overwrite mode)

Delete a bookmark

Rate limiting

Tag Audit Mode

Overview

Step 1: Fetch all bookmarks

Step 2: Analyze tag issues

Step 3: Present issues in batches

Step 4: Apply confirmed changes

Step 5: Summary

Dead Link Detection Mode

Overview

Step 1: Fetch all bookmarks

Step 2: Check links in batches

Step 3: Present results

Step 4: Apply user decisions

Step 5: Summary

Timeliness Check Mode

Overview

Step 1: Fetch all bookmarks

Step 2: Heuristic pre-filtering

Filter 1: Tag filter (tech only)

Filter 2: Age filter

Filter 3: Version detection

Candidate condition

Step 3: Content fetching via Jina Reader

Step 4: AI timeliness analysis

Step 5: Batch presentation

Step 6: Apply user actions

Step 7: Summary

Common Errors