calibre-metadata-apply

A skill for updating metadata of existing Calibre books.

Skill selection contract (strict)

• If the user intent is metadata edit/fix/update, this skill is mandatory.
• If the request mentions ID-based title fix (e.g. ID1011 タイトル修正), this skill is mandatory.
• calibre-catalog-read must not be used for those edit intents.

Use this skill when the user asks any of: - "ID指定でタイトル修正" - "メタデータ編集" - title/authors/series/series_index/tags/publisher/pubdate/languages updates

Do NOT route those requests to calibre-catalog-read.

Requirements

• calibredb must be available on PATH in the runtime environment
• subagent-spawn-command-builder installed (for spawn payload generation)
• pdffonts is optional/recommended for PDF evidence checks
• Reachable Calibre Content server URL
• http://HOST:PORT/#LIBRARY_ID
• If LIBRARY_ID is unknown, use #- once to list available IDs on the server.
• --with-library can be omitted only when one of these is configured:
• env: CALIBRE_WITH_LIBRARY or CALIBRE_LIBRARY_URL or CALIBRE_CONTENT_SERVER_URL
• config: ~/.config/calibre-metadata-apply/config.json with with_library
• optional library id completion: CALIBRE_LIBRARY_ID or config library_id
• Host failover (IP change resilience):
• Optional env: CALIBRE_SERVER_HOSTS=host1,host2,...
• Script auto-tries candidates, including WSL host-side nameserver from /etc/resolv.conf.
• If authentication is enabled, prefer /home/altair/.openclaw/.env:
• CALIBRE_USERNAME=<user>
• CALIBRE_PASSWORD=<password>
• Auth scheme policy for this workflow:
• Non-SSL deployment assumes Digest authentication.
• Do not pass auth mode arguments such as --auth-mode / --auth-scheme.
• Pass --password-env CALIBRE_PASSWORD (username auto-loads from env)
• You can still override explicitly with --username <user>.
• Optional auth cache: --save-auth (default file: ~/.config/calibre-metadata-apply/auth.json)

Supported fields

Direct fields (set_metadata --field)

• title
• title_sort
• authors (string with & or array)
• author_sort
• series
• series_index
• tags (string or array)
• publisher
• pubdate (YYYY-MM-DD)
• languages
• comments

Helper fields

• comments_html (OC marker block upsert)
• analysis (auto-generates analysis HTML for comments)
• analysis_tags (adds tags)
• tags_merge (default true)
• tags_remove (remove specific tags after merge)

Required execution flow

A. Target confirmation (mandatory)

1. Run read-only lookup to narrow candidates
2. Show id,title,authors,series,series_index
3. Get user confirmation for final target IDs
4. Build JSONL using only confirmed IDs

B. Proposal synthesis (when metadata is missing)

1. Collect evidence from file extraction + web sources
2. Show one merged proposal table with:
3. candidate, source, confidence (high|medium|low)
4. title_sort_candidate, author_sort_candidate
5. Get user decision:
6. approve all
7. approve only: <fields>
8. reject: <fields>
9. edit: <field>=<value>
10. Apply only approved/finalized fields
11. If confidence is low or sources conflict, keep fields empty

C. Apply

1. Run dry-run first (mandatory)
2. Run --apply only after explicit user approval
3. Re-read and report final values

Analysis worker policy

• Use subagent-spawn-command-builder to generate sessions_spawn payload for heavy candidate generation
• task is required.
• Profile should include model/thinking/timeout/cleanup for this workflow.
• Use lightweight subagent model for analysis (avoid main heavy model)
• Keep final decisions + dry-run/apply in main

Data flow disclosure

• Local execution:
• Build calibredb set_metadata commands from JSONL.
• Read/write local state files (state/runs.json) and optional auth/config files under ~/.config/calibre-metadata-apply/.
• Subagent execution (optional for heavy candidate generation):
• Uses sessions_spawn via subagent-spawn-command-builder.
• Text/metadata sent to subagent can reach model endpoints configured by runtime profile.
• Remote write:
• calibredb set_metadata updates metadata on the target Calibre Content server.

Security rules: - Do not use --save-plain-password unless explicitly instructed by the user. - Prefer env-based password (--password-env CALIBRE_PASSWORD) over inline --password. - If user does not want external model/subagent processing, keep flow local and skip subagent orchestration. - In agent/chat execution, do not call calibredb directly for edit operations. - Always execute node skills/calibre-metadata-apply/scripts/calibredb_apply.mjs. - Never run calibre-server from this skill. - This workflow always targets an already-running Calibre Content server.

Connection bootstrap (mandatory)

• Do not ask the user for --with-library first.
• First, execute using saved defaults (env/config) with no explicit --with-library.
• Scripts auto-load .env and resolve CALIBRE_WITH_LIBRARY / CALIBRE_CONTENT_SERVER_URL.
• Ask user for URL only when command output shows unresolved connection, such as:
• missing --with-library
• unable to resolve usable --with-library
• repeated connection failures for all candidates

Long-run turn-split policy (library-wide)

For library-wide heavy processing, always use turn-split execution.

Unknown-document recovery flow (M3)

Batch sizing rule: - Keep each unknown-document batch small enough to show full row-by-row results in chat (no representative sampling). - If unresolved items remain, stop and wait for explicit user instruction to start the next batch.

User intervention checkpoints (fixed)

1. Light pass (metadata-only)
2. Always run this stage by default (no extra user instruction required)
3. Analyze existing metadata only (no file content read)
4. Present a table to user:
   • current file/title
   • recommended title/metadata
   • confidence/evidence summary

5. Stop and wait for user instruction before any deeper stage

6. On user request: page-1 pass

7. Read only the first page and refine proposals

8. Report delta from light pass

9. If still uncertain: deep pass

10. Read first 5 pages + last 5 pages
11. Add web evidence search

12. Produce finalized proposal with confidence + rationale

13. Approval gate

14. Show detailed findings and request explicit approval before apply

Pending and unsupported handling

• Use pending-review tag for unresolved/hold items.
• If document is unresolved in current flow, do not force metadata guesses.
• Tag with pending-review and keep for follow-up investigation.

Diff report format (for unknown batch runs)

Return full results (not samples): - execution summary (target/changed/pending/skipped/error) - full changed list with id + key before/after fields - full pending list with id + reason - full error list with id + error summary - confidence must be expressed as high|medium|low

Runtime artifact policy

• Keep run-state and temporary artifacts only while a run is active.
• On successful completion, remove per-run state/artifacts.
• On failure, keep minimal artifacts only for retry/debug, then clean up after resolution.

Internal orchestration (recommended)

• Use lightweight subagent for all analysis stages
• Keep apply decisions in main session
• Persist run state for each stage in state/runs.json

Turn 1 (start)

1. Main defines scope
2. Main generates spawn payload via subagent-spawn-command-builder (profile example: calibre-meta), then calls sessions_spawn
3. Save run_id/session_key/task via scripts/run_state.mjs upsert
4. Immediately tell the user this is a subagent job and state the execution model used for analysis
5. Reply with "analysis started" and keep normal chat responsive

Turn 2 (completion)

1. Receive subagent completion notice
2. Save result JSON
3. Complete state handling via scripts/handle_completion.mjs --run-id ... --result-json ...
4. Return summarized proposal (apply only when needed)

Run state file: - state/runs.json

PDF extraction policy

1. Try ebook-convert first
2. If empty/failed, fallback to pdftotext
3. If both fail, switch to web-evidence-first mode

Sort reading policy

• Use user-configured reading_script for Japanese/non-Latin sort fields
• katakana / hiragana / latin
• Ask once on first use, then persist and reuse
• Default policy is full reading (no truncation)
• Config path: ~/.config/calibre-metadata-apply/config.json
• key: reading_script

Usage

Dry-run:

cat changes.jsonl | node skills/calibre-metadata-apply/scripts/calibredb_apply.mjs 
  --with-library "http://127.0.0.1:8080/#MyLibrary" 
  --password-env CALIBRE_PASSWORD 
  --lang ja

Dry-run (when default library is preconfigured via env/config):

cat changes.jsonl | node skills/calibre-metadata-apply/scripts/calibredb_apply.mjs 
  --password-env CALIBRE_PASSWORD 
  --lang ja

Apply:

cat changes.jsonl | node skills/calibre-metadata-apply/scripts/calibredb_apply.mjs 
  --with-library "http://127.0.0.1:8080/#MyLibrary" 
  --password-env CALIBRE_PASSWORD 
  --apply

Do not

• Do not run direct --apply using ambiguous title matches only
• Do not include unconfirmed IDs in apply payload
• Do not auto-fill low-confidence candidates without explicit confirmation
• Do not start a local server with guessed path like ~/Calibre Library