| name | source-tracker |
| description | Persistent citation database for multi-session research. Add URLs as they're cited, dedup variants, tag by topic, check link health, and export bibliographies in Markdown/BibTeX/CSV/JSON. |
| version | 1.0.0 |
| author | moonlight-lupin |
| license | MIT |
| platforms | ["linux","macos","windows"] |
| metadata | {"tags":["citation","bibliography","research","sources","dedup","url-tracking","link-health"],"related_skills":["deep-research","notebooklm-mode","entity-research"]} |
Source Tracker
Overview
Source Tracker is a small persistent citation manager for research workflows.
Research sources often scatter across browser tabs, notes, temporary files, and
separate sessions. URLs get cited once and then disappear, duplicates accumulate
as http/https or www variants, and bibliography export becomes a manual
cleanup job at the end.
This skill fixes that by keeping a portable SQLite database of every cited URL:
add sources as soon as they are cited, tag them by topic, deduplicate URL
variants, re-check stale links, and export bibliographies in Markdown, BibTeX,
CSV, or JSON.
The database path is configurable with --db-path or the
SOURCE_TRACKER_DB environment variable. If neither is set, commands use
./sources.db relative to the current working directory.
Quick Start
From the skill directory:
python scripts/source_db.py add --url URL --topic TOPIC
A practical example:
python scripts/source_db.py add \
--url "https://example.org/report" \
--topic "battery supply chain" \
--title "Example Battery Report" \
--notes "Baseline market-size estimate" \
--type report
Use a persistent project database when research spans folders or sessions:
export SOURCE_TRACKER_DB="$HOME/research/sources.db"
python scripts/source_db.py add --url "https://example.org" --topic "market scan"
Or pass the path explicitly:
python scripts/source_db.py --db-path "$HOME/research/sources.db" add --url "https://example.org" --topic "market scan"
Workflows
1. Add Sources
Add every URL at the moment it becomes a cited source. Always include a topic.
Use a source type when the material is not a normal web page.
python scripts/source_db.py add \
--url "https://example.com/article#section" \
--topic "ai regulation" \
--title "Example Article" \
--notes "Defines the enforcement timeline" \
--type news \
--session-id "research-2026-07-06"
If --title is omitted, the script tries a best-effort GET request and parses
<title>. If that fetch fails, the source is still added with a blank title.
Completion criterion: the command prints a JSON object with inserted: true for
a new row or inserted: false for an exact canonical URL already in the DB.
2. Search Sources
Search by topic and optional filters. Results are JSON so they can be piped into
other tools.
python scripts/source_db.py search --topic "ai regulation"
Filter by date range:
python scripts/source_db.py search \
--topic "ai regulation" \
--from 2026-01-01 \
--to 2026-12-31
Filter by source type and verification status:
python scripts/source_db.py search \
--topic "ai regulation" \
--type report \
--verified true
Completion criterion: the JSON array contains only records matching the topic
and filters.
3. Deduplicate URL Variants
Run dedup after a research burst or before export. It merges common URL variants
such as http vs https, www. vs bare host, fragment-only differences, and
trailing slash differences.
python scripts/source_db.py dedup
Completion criterion: the command prints a JSON summary with merged_groups,
removed_rows, and removed_ids. The survivor keeps the earliest accessed_at
and combines non-empty notes from all merged rows.
4. Export Bibliographies
Export a topic bibliography. If --output is omitted, content prints to stdout.
If --output is set, provide the file path to the user.
Markdown:
python scripts/source_db.py export \
--topic "ai regulation" \
--format markdown \
--output ai-regulation-sources.md
BibTeX:
python scripts/source_db.py export \
--topic "ai regulation" \
--format bibtex \
--output ai-regulation-sources.bib
CSV:
python scripts/source_db.py export \
--topic "ai regulation" \
--format csv \
--output ai-regulation-sources.csv
JSON:
python scripts/source_db.py export \
--topic "ai regulation" \
--format json \
--output ai-regulation-sources.json
Completion criterion: the output contains every source for the topic, sorted by
topic/title/date, in the requested format.
5. Health Check
Run link health checks manually before a final report or from a cron scheduler.
The checker uses HEAD requests, marks HTTP 200-399 as alive, updates
last_checked, and flags dead links by setting verified = 0.
python scripts/url_health.py --stale-days 30 --timeout 10 --batch-size 50
With an explicit database path:
python scripts/url_health.py \
--db-path "$HOME/research/sources.db" \
--stale-days 7 \
--timeout 5 \
--batch-size 100
Completion criterion: the command prints Checked N URLs: M alive, K dead and
exits with code 0. Dead links are recorded in the database; they are not treated
as runtime errors.
6. Stats and Topic Inventory
Show source counts by topic, type, and verification status:
python scripts/source_db.py stats
List all topic tags:
python scripts/source_db.py list-topics
Completion criterion: stats print as JSON and topic inventory prints a JSON
array of distinct topic strings.
URL Normalization Rules
Source Tracker uses two levels of URL handling:
-
Canonical storage URL
- Lowercase scheme and host.
- Strip URL fragments such as
#section.
- Strip trailing slash on non-root paths.
- Preserve query strings.
- Preserve
www. because it may be the URL the user expects to see.
-
Dedup comparison key
- Applies all canonical storage rules.
- Treats
http and https variants as the same source.
- Strips a leading
www. prefix from the host for comparison only.
Examples:
| Input | Canonical URL | Dedup comparison |
|---|
HTTPS://WWW.Example.com/Page/#intro | https://www.example.com/Page | //example.com/Page |
http://example.com/ | http://example.com/ | //example.com/ |
https://www.example.com | https://www.example.com/ | //example.com/ |
Source Types
Use one of these values with --type:
| Type | Use for |
|---|
web | Standard web pages, documentation pages, blog posts, landing pages. |
pdf | Direct PDF URLs or pages where the source of record is a PDF. |
api | API endpoints, JSON/XML data endpoints, machine-readable service output. |
dataset | Data downloads, CSV/Parquet repositories, public data catalogs. |
book | Online books, book chapters, scans, or bibliographic pages for books. |
news | News articles, wire reports, interviews, live blogs. |
report | White papers, government reports, analyst reports, institutional reports. |
Research Workflow Integration
Deep Research
During iterative search/extract/synthesize work, add a source immediately after
it passes the quality filter and before using it in the synthesis:
python scripts/source_db.py add \
--url "SOURCE_URL" \
--topic "PROJECT_TOPIC" \
--title "SOURCE_TITLE" \
--notes "Supports sub-question: ..." \
--session-id "SESSION_ID"
Before the final report:
python scripts/source_db.py dedup
python scripts/source_db.py export --topic "PROJECT_TOPIC" --format markdown --output bibliography.md
Notebook-style Source Vaults
When building a source vault, add each source as it enters the vault. Store the
vault or corpus identifier in --session-id, and use notes for coverage labels
such as primary evidence, background, or contradiction.
python scripts/source_db.py add \
--url "SOURCE_URL" \
--topic "VAULT_TOPIC" \
--notes "Vault source 007; primary evidence" \
--session-id "vault-007"
Entity Research
For entity dossiers, tag sources with the entity name plus the research lens.
Use source types to distinguish official registries, adverse media, reports, and
datasets.
python scripts/source_db.py add \
--url "SOURCE_URL" \
--topic "Acme Ltd adverse media" \
--type news \
--notes "Allegation source; not independently verified"
Cron Usage
Run weekly health checks with the cron scheduler. Example crontab entry:
0 9 * * 1 cd /path/to/source-tracker && SOURCE_TRACKER_DB=/path/to/sources.db python scripts/url_health.py --stale-days 30 --batch-size 100 >> /path/to/source-health.log 2>&1
Use small batches for very large databases to avoid long scheduler jobs:
0 9 * * 1 cd /path/to/source-tracker && python scripts/url_health.py --db-path /path/to/sources.db --stale-days 30 --batch-size 50
Output Formats
- Markdown bibliography — grouped by topic, with each source rendered as
- [Title](URL) — notes (accessed_at).
- BibTeX —
@misc{key, title={...}, url={...}, note={...}, urldate={...}}.
- CSV —
id,url,title,topic,source_type,accessed_at,notes,verified,last_checked.
- JSON — array of full source objects, including
session_id and normalized
URL fields.
See references/export-formats.md for concrete examples.
Common Pitfalls
- Invented URLs — never add a URL unless it came from a web search tool,
web extraction tool, user-provided source, or another verifiable source
channel. If a URL was guessed, verify it before adding it.
- Missing topic tags —
--topic is required for a reason. Use consistent
topic names so search, stats, and export do not fragment across near-duplicates.
- Stale health checks —
verified = 1 means the source was alive at its
last check, not that it is alive forever. Run url_health.py before final
delivery for long-running projects.
- Duplicate variants —
https://www.example.com/, http://example.com,
and https://example.com#intro can refer to the same source. Run dedup
before export.
- Blank titles — title extraction is best-effort. For important citations,
pass
--title explicitly instead of relying on a remote page fetch.
- Relative database confusion — the default
./sources.db depends on the
current working directory. Use SOURCE_TRACKER_DB or --db-path for
long-running projects.
Verification Checklist