Investigate a LinkedIn-MCP issue

Evaluate the reporter packet and the matching source. A live LinkedIn call is optional. Do not check out a PR or attempt a fix. That is /3-verify-pr-fix.

1. Read the issue

NUM=$(echo "$ARGUMENTS" | sed -E 's|.*/||; s|#||g' | grep -oE '^[0-9]+' | head -1)
[ -z "$NUM" ] && { echo "Invalid input: '$ARGUMENTS'. Pass an issue number or URL." >&2; exit 1; }
REPO=stickerdaniel/linkedin-mcp-server

gh issue view $NUM --repo $REPO --comments

From the thread extract the tool, arguments, observed result, runtime, LinkedIn variant, and related issues. Distinguish observations, source findings, hypotheses, and work not run.

Map the tool to code:

1. linkedin_mcp_server/tools/<surface>.py. MCP entrypoint and arg validation
2. docs/linkedin-architecture.md. Generated ownership table; follow it to linkedin_mcp_server/linkedin/<owner>.py rather than treating linkedin/extractor.py as the implementation
3. linkedin_mcp_server/linkedin/fields.py. PERSON_SECTIONS / COMPANY_SECTIONS (each entry = one navigation)
4. The owner-local test, usually tests/linkedin/test_<owner>.py; use tests/test_fields.py, tests/test_identifiers.py, and tests/test_link_metadata.py for those owners, and tests/linkedin/test_facade_*.py only for facade contracts

2. Packet and source

Inspect the relevant source at the current SHA. Do not invent a LinkedIn result or an unimplemented tool call.

This step is complete when the report names the issue, the code SHA, the inspected evidence, the facts established, the unverified runtime claims, and the next decision.

Use one of:

• supported by reporter evidence
• confirmed in source
• needs more evidence (list the specific missing fields)
• not supported by the supplied evidence