hunter-tracker
Skill12 starsChanged 28 days agoMITView on GitHub
Pipeline Tracker. Tracks every role, contact and next step in one pipeline: hunter/pipeline.json, the single file every hunter skill reads and writes. Adds and updates roles and contacts, moves roles through the stages (saved, applied, screen, interview, onsite, offer, rejected, withdrawn), shows a summary by stage, what is coming up this week, what has gone stale, and exports CSV for a spreadsheet. Owns the pipeline schema and validates it after every change. Use when the user says "show my pipeline", "where am I with each application", "add this job", "I applied", "I got an interview", "I got rejected", "what's next", "what's stale", "export my applications", or "track this".
In this repository10 other files it gives its agents.
- hunter-applySkill
- hunter-connectorSkill
- hunter-coverSkill
- hunter-followupSkill
- hunter-interviewSkill
- hunter-linkedinSkill
- hunter-researchSkill
- hunter-resumeSkill
- hunter-salarySkill
- hunter-scoutSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 6 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 39
Every command takes --file (default hunter/pipeline.json) and --today YYYY-MM-DD where dates matter, so results are reproducible.
- Very specific: line 93
After any skill writes, run validate.
- Very specific: line 101
When the user asks where things stand: summary.
- Distinctive: line 138
Never sends anything or contacts anyone: it is a record.
- Distinctive: line 139
Never guesses a date, a stage or a reply the user did not report.
- Distinctive: line 140
Never stores private information about a contact: public professional facts only.
- Distinctive: line 149
No bulk or automated messaging, no scraping behind logins, no tricks around a site's limits.
- Distinctive: line 155
Stop rules: stop at the first "no" or any sign of disinterest, max 2 follow-ups, no message after 21 days of silence, and a request to stop …
- Distinctive: line 157
Never invent experience, titles, degrees, dates or numbers: rewrite and reorder what is true, and ask when something is missing.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
hunter-tracker
The Pipeline Tracker is the memory of the whole search. Every other hunter skill
reads hunter/pipeline.json and writes its part back; this skill owns the file's
shape and checks it.
${CLAUDE_SKILL_DIR} below is this skill's folder (where this SKILL.md lives).
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" init
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" add-role --company Google --title "Software Engineer" --url <posting URL>
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" move google-software-engineer applied --today 2026-10-23
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" update-role google-software-engineer --next-step "Recruiter screen" --next-date 2026-10-30
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" add-contact --name "Maya C." --company Google --role "Engineering Manager"
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" summary --today 2026-10-16
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" next --today 2026-10-16 --days 7
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" stale --today 2026-10-16 --days 14
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" show google-software-engineer
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" export --what roles --out hunter/pipeline-roles.csv
python3 "${CLAUDE_SKILL_DIR}/pipeline.py" validateEvery command takes --file (default hunter/pipeline.json) and --today
YYYY-MM-DD where dates matter, so results are reproducible.
The schema (this skill owns it)
{ "roles": [ {"id", "company", "title", "url", "stage", "applied", "next_step", "next_date", "notes"} ],
"contacts": [ {"id", "name", "role", "company", "linkedin", "email", "email_confidence", "source", "notes"} ],
"threads": [ {"contact_id", "role_id", "channel",
"messages": [ {"date", "direction": "out|in", "text"} ],
"status", "next_followup"} ] }- stages: saved, applied, screen, interview, onsite, offer, rejected, withdrawn.
- thread status: drafted, sent, replied, booked, declined, closed.
- dates:
YYYY-MM-DD. A message date may carry a time (2026-10-12T09:30). - ids: roles
company-title(google-software-engineer), contactsname-company(maya-c-google); a clash gets-2. Ids from/hunter-scoutare kept as they are. - email_confidence: a number from 0 to 1 (a pattern guess from
/hunter-connector), or high, medium, low, unknown, orpublished.published(orverified) is only valid whensourceis the URL of the public page where the address appears; everything else is a guess. - channel: email, linkedin, phone, in-person or other.
- optional fields kept by
/hunter-connector(part of the schema): threadinvite(true while a LinkedIn invitation is pending; it gets no follow-up), threaddraft({"kind", "subject", "text", "created", "hash"}, a message waiting for the user's yes), threadapproval({"reply", "date", "hash"}, that yes word for word), threadbooked({"when", "minutes", "where"}), and contactdo_not_contact(true after a stop request: never contacted again). - a pending draft is never in
messages:messagesholds only what really went out or came in. (A hand-made file may instead flag a message"draft": trueor use statusdraftedwith the draft as its last outgoing message; both are read the same way.) - notes: free text; the tool appends dated lines (
2026-10-16: applied -> screen) so the history stays readable. "DO NOT CONTACT" in a contact's notes closes every thread with them for good. - Missing lists are read as empty. Top-level keys starting with
_are comments. Any other extra field is kept and reported as a warning.
validate exits 1 on an error (unknown stage or status, bad date, a thread pointing
at a contact or role that does not exist, duplicate ids, an invalid email, a
"published" email with no source URL) and lists warnings (no applied date on an
applied role, a follow-up date on a closed thread, messages out of order).
Who writes what
| skill | writes |
/hunter-scout | new roles at stage saved, from hunter/jobs.json |
/hunter-resume, /hunter-cover | a dated note on the role |
/hunter-apply | a note that the application is filled and waiting for the user; move ... applied once the user submits |
/hunter-connector | contacts and threads: drafted, sent, replied, booked |
/hunter-followup | follow-ups it recorded after the user's yes, replies, stop requests |
/hunter-interview, /hunter-salary | next steps and dates |
After any skill writes, run validate.
Steps
- First time:
init, then add what the user already has in flight (roles they applied to, people they talk to). Ask for the applied dates; do not guess them. - Each time something happens, update it right away:
movefor a stage change,update-role --next-step ... --next-date ...for the next action. - When the user asks where things stand:
summary. It shows counts by stage, the next 7 days (overdue first) and stale roles: active, nothing scheduled, no activity in 14 days. - For a spreadsheet:
export --what roles(or contacts, threads) and the user opens the CSV in Google Sheets or Excel.
Example: Jordan's pipeline on 2026-10-16
pipeline.example.json is the reel's story: five roles at the hardest companies,
Maya C. at Google, the email thread booked for coffee and the LinkedIn request.
Pipeline on 2026-10-16: 5 roles (5 active, 2 applied), 1 contact
By stage:
saved 3
applied 1
screen 1
Conversations: 1 sent, 1 booked
Next 7 days:
2026-10-19 Amazon, Software Development Engineer II: Online assessment
2026-10-19 Meta, Software Engineer, Product: Tailor the resume (hunter-resume)
2026-10-22 Google, Software Engineer: Coffee chat with Maya C. (Google Meet, 10:00)
Stale (no activity and nothing scheduled):
netflix-senior-software-engineer (Netflix, saved): 22 days idle
nvidia-deep-learning-software-engineer (NVIDIA, applied): 16 days idleThe Google role is still "saved": the application is filled but not sent, and the coffee chat comes first. That is the point of the reel: an in at the company before the application goes out.
What it never does
- Never sends anything or contacts anyone: it is a record.
- Never guesses a date, a stage or a reply the user did not report.
- Never stores private information about a contact: public professional facts only.
Consent and truth
- Nothing is sent or submitted without the user's explicit yes for that exact message or application. Claude drafts, the user approves, then it goes out from the user's own accounts: email as a Gmail draft first; LinkedIn messages through Claude in Chrome with the user present, one at a time, at human pace, the user clicking Send; application forms filled and left for the user to submit.
- No bulk or automated messaging, no scraping behind logins, no tricks around a site's limits. LinkedIn's terms forbid bots and automated messaging.
- Contact research uses public professional information only (the person's public profile, talks, posts, papers, the company site), never personal life, family, home address or private accounts. Email addresses are guesses from public patterns, marked with a confidence, never called verified unless found published.
- Stop rules: stop at the first "no" or any sign of disinterest, max 2 follow-ups, no message after 21 days of silence, and a request to stop is honoured forever.
- Never invent experience, titles, degrees, dates or numbers: rewrite and reorder what is true, and ask when something is missing.
- Salary benchmarks and interview material cite their sources. Nothing here guarantees an offer or an outcome.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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- It worked
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

