LLMSkillHub
mirroredCopied from selfishprimate/seekter under MIT. selfishprimate has not claimed this page, and is not affiliated with LLM SkillHub.

selfishprimate / seekter-report

Summarise the job search from the markdown tracker - funnel, response rate, what's working, where applications come from, what's pending on the user. Use when the user runs /seekter-report or asks how the search is going, for weekly numbers, or what to change.

0
SKILL.md
1.7 KB

/seekter-report — how is the search going

Read-only. Data comes from applications/ via scripts/seekter.py, plus runs/*.md for per-day source tables.

  1. python3 scripts/seekter.py stats (all time) and python3 scripts/seekter.py stats --since <7 days ago>.
  2. python3 scripts/seekter.py list --since <period start>, then read the front matter of the rows you need (source, ats, location_fit, fit).

  3. Compute, for the period and all time:

    • applications sent, skips, pending hand-offs;
    • replies: interviewing + offer + rejected, as a share of sent; median days from applied to the first log line after it;
    • by source (freehire, linkedin, board names, manual): sent and replies;
    • by location_fit (A/B/C): sent and replies. A track with many sends and no replies is a targeting signal;
    • top skip reasons (group the Reason column of applications/<YYYY-MM>/skipped.md by its first clause).
  4. Every record with status: pending is a hand-off (python3 scripts/seekter.py list --status pending; also the "Needs you" table in applications/README.md): list each with its link and the exact action.
  5. Write 3–5 plain observations with the number behind each ("C-track: 14 sent, 0 replies in 3 weeks"). Suggest at most two changes, each tied to a file (profile/settings.json query, profile/profile.md rule). Don't change them without the user saying yes.

Save as runs/report-<YYYY-MM-DD>.md and show the user the short version.