CSPR Interest Profiler

Infer and refresh cspr user preference memory from browser-history evidence, notes, and feedback.

interest-profiler

Use this skill when a user initializes cspr or asks to refresh personalization.

Workflow:

0. If the run folder has no history artifact, create it with:

   interest-scan browser --out RUN/history_evidence.json

1. Compact the raw history before reading it:

   interest-scan compact --in RUN/history_evidence.json --out RUN/history_context.json

2. Export the complete local seen-URL set for tool filtering:

   interest-scan seen --in RUN/history_evidence.json --out RUN/seen_urls.jsonl

   When a CSPR home is available, pass --home HOME so browser-history URLs are also recorded into persistent read memory at HOME/state/read_items.jsonl.

3. Infer repeated creators and source preferences:

   source-infer from-history --in RUN/history_evidence.json --out RUN/potential_sources.yaml

4. Read the current run folder's history_context.json and potential_sources.yaml. Avoid reading raw history_evidence.json unless the user asks for detailed inspection. Do not read seen_urls.jsonl into the model context unless debugging a specific filter issue.

5. Read ~/.cspr/memory/notes.md and ~/.cspr/state/feedback.jsonl if present.

6. Infer durable interests, short-term interests, disliked patterns, and source preferences.

7. Write a complete profile.yaml into the run folder.

8. Apply it with:

   prefmem update --in RUN/profile.yaml

Keep the user experience quiet. Do not ask for profile approval unless the user explicitly requests review.

Do not write search_queries into profile memory. Search queries are run-specific and should be generated fresh by source-scout from durable interests.