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SKILL verified MIT Self-run

Fetch Meta To Kb

skill-tiangong-ai-agent-skills-fetch-meta-to-kb · by tiangong-ai

Fetch journal articles from Crossref published after a user-specified date and insert them into PostgreSQL `journals` with DOI deduplication. Use when incrementally ingesting journal metadata from `journals_issn` into `journals`.

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Install

$ agentstack add skill-tiangong-ai-agent-skills-fetch-meta-to-kb

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • ✓ Prompt-injection patterns
  • ✓ Secret / credential exfiltration
  • ✓ Dangerous shell & filesystem operations
  • ✓ Untrusted network calls
  • ✓ Known-malicious package signatures

What it can access

  • ✓ Network access No
  • ✓ Filesystem access No
  • ✓ Shell / process execution No
  • ✓ Environment & secrets No
  • ✓ Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

✓ Security review passed
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● 12d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Fetch Meta to KB

Core Goal

  • Pull journal-article records from Crossref after a given --from-date.
  • Read ISSN seed rows from journals_issn (journal, issn1).
  • Insert rows into journals with ON CONFLICT (doi) DO NOTHING.
  • Keep the implementation aligned with fetch_meta_to_kb.py.

Run Workflow

  1. Set database connection env vars (user-managed keys prefixed with KB_):
  • KB_DB_HOST
  • KB_DB_PORT
  • KB_DB_NAME
  • KB_DB_USER
  • KB_DB_PASSWORD
  • KB_LOG_DIR (required, log output directory)
  1. Run incremental fetch with a required date:
python3 scripts/fetch_meta_to_kb.py --from-date 2024-05-01
  • If executing through an exec tool call, set timeout to 1800 seconds (30 minutes).
  1. Check logs in:
  • ${KB_LOG_DIR}/fetch-meta-to-kb-YYYYMMDD-HHMMSS.log (UTC timestamp, one file per run)
  1. Build user-facing summary strictly from the current run output:
  • Prefer RUN_SUMMARY_JSON emitted by fetch_meta_to_kb.py.
  • If JSON is unavailable, parse only this run's ${KB_LOG_DIR}/fetch-meta-to-kb-YYYYMMDD-HHMMSS.log.
  • total_inserted must mean rows inserted in this run (after DOI dedup), not cumulative rows in table.

Behavior Contract

  • Query Crossref endpoint: https://api.crossref.org/journals/{issn}/works.
  • Filter with type:journal-article,from-pub-date:.
  • Keep only items whose container-title equals target journal title (case-insensitive).
  • Continue pagination with cursor until no matching items remain.
  • Store fields in journals: title, doi, journal, authors, date, abstract (nullable when Crossref has no abstract).
  • Reporting/announcement metrics must use current-run log/summary only.
  • Do not compute announcement counts via database-wide or time-window SQL such as WHERE date >= ....

Scope Boundary

  • Implement only Crossref incremental fetch + insert into journals.

Script

  • scripts/fetch_meta_to_kb.py

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.

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