/job-hunt

• Between Step 3 fetcher return → Step 7: No text output is allowed. Text output = turn end = wait for user = process interruption
• Immediately call the tool (Skill / Bash / Read / Write) required for the next step after each step ends, without inserting any text
• The return results of sub-skills (fetcher / analyzer / tailor) are internal data, must not be echoed, repeated, or reported to the user, and should be directly used for the next step
• Prohibited to ask the user "whether to continue" or "whether to start the next step" between steps

<data_dir>/.work/resume.md

• User sends new resume → process according to the "If not exists" method below, overwrite and save

  resume.md

  , enter Step 2.5 for re-evaluation
• User says "Continue" or other non-resume content → skip this step, skip Step 2.5, directly enter Step 3

/Users/xxx/resume.md

• Send file (.md) / file path (.md): Read the file content using Read tool or Bash
• Send file / file path (other formats, such as .pdf / .docx / .doc / .txt / .rtf, etc.): Do not attempt any form of parsing, directly inform the user:
  "PDF / Word and other layout file uploads are not supported temporarily (cross-environment parsing is prone to distortion). Please use: ① Open the resume with any PDF/Word reader, select all (Cmd/Ctrl+A) → copy (Cmd/Ctrl+C) → paste here and send ② Or save the resume as .md format and resend"
  Stop execution and wait for the user to re-operate
• Paste text: Execute according to the "Pasted Text Processing Flow" below

<data_dir>/.work/resume.md

• Contains ≥ 2 section markers (line starts with

  #

  ,

  ##

  or ordered list numbers like

  1.

  /

  2.

  )
• Contains ≥ 2 list markers (line starts with

  -

  or

  *

  or

  +

  followed by a space)
• Average non-empty line length ≥ 15 characters (indicating no forced line breaks per word)
• No large number of "single-word isolated lines" (more than 5 consecutive lines with only 1-3 characters per line)

<data_dir>/.work/resume.md

1. Must output the complete original resume text pasted by the user (no omissions, not a preview, not a summary, not truncated to first N words)
2. The A/B question comes after the resume original text
3. The A/B question must be the last paragraph of the entire message, so that the user's last line of sight falls on

   👉 Reply A or B

4. Do not write any explanatory text above the resume original text (such as "The following is your resume" "Received" and other opening remarks)
5. Display the resume original text in a code block (wrapped with ```) to avoid Markdown rendering interfering with the original format

```
<Complete original resume text pasted by the user, unchanged>
```

---

📝 The above is the resume content you pasted. It seems there are some format issues - there may be line breaks, missing section markers, etc., which are common when copying from PDF/Word.

Two processing methods:

A. **Help me organize it** —— Only modify the format: merge broken lines of the same paragraph, restore project symbols, add section titles; **do not change a single word**
B. **Keep my original format** —— I want it this way, don't change it

👉 Reply A or B

• Truncate resume content (even if the resume is very long, post it in full)
• Append any text after the A/B question
• Add any title/explanation above the resume original text (start directly with the code block)

• User replies A (or semantic equivalents: "organize", "clean", "help me fix", "whatever", etc.) → enter Step 5 for structure normalization
• User replies B (or semantic equivalents: "don't change", "keep as is", "retain", "don't modify", etc.) → write the original content into

  <data_dir>/.work/resume.md

  , inform the user "✅ Saved according to your original format.", enter Step 2.5
• User replies ambiguous content (such as "?" "What do you mean") → briefly re-explain the meaning of A/B once, then wait for reply
• User directly sends a new resume → treat as re-pasting, return to Step 1

Responsible for Douyin\nshort videos\nfrontend development

Responsible for Douyin short videos frontend development

。！？.!?

Zhang\nSan

Zhang San

Work\nExperience

Work Experience

·

●

▪

◦

▶

- 

## 

​

­

• Add, delete, or rewrite any text content (even a single word)
• Correct typos (if the user writes "Hangzhou" as "杭洲", keep "杭洲")
• Translate, summarize, simplify, or expand
• Infer and fill in missing information based on context
• Add sections, skills, or experiences not mentioned by the user
• Change the order, time, or numbers of events

• Write the cleaned result into

  <data_dir>/.work/resume.md

• Briefly inform the user of the cleaning amount: "📝 Resume format organized: merged N broken lines / restored M project symbols / added K section titles. The original version has been backed up (say 'restore original version' if unsatisfied)."
• Enter Step 2.5

1. Check if

   <data_dir>/.work/resume.raw.md

   exists
   • Does not exist → inform "Original backup version not found (maybe this resume was not cleaned). If you need to replace it, directly re-paste or send a new resume."
   • Exists → use Bash to copy

     resume.raw.md

     and overwrite

     resume.md

2. Inform the user "✅ Switched back to the original version."
3. Re-enter Step 2.5 for evaluation

<data_dir>/.work/resume.md

• Before any evaluation action, must complete the complete screening process of Rule 1→2→3
• Must not infer the work content of the experience based on company name, position name, or department name for evaluation —— The evaluation object can only be the action verbs and result descriptions written clearly in the resume
• Only the text content that passes Rule 3 can appear in the "Paragraph-by-Paragraph Analysis"; blocks/lines that fail the screening must not appear

• Personal Information / Basic Information / Contact Information
• Professional Skills / Skill Strengths / Technical Abilities / Tool Usage / Technology Stack
• Educational Background / Educational Experience / Academic Qualification
• Self-evaluation / Personal Profile / Job Intention
• Certificates / Awards / Honors

• No action verbs (responsible for, led, designed, promoted, built, optimized, completed, implemented, led, etc.)
• No result descriptions (improved, reduced, increased, decreased, reached, exceeded, saved, or specific numbers/percentages)

• "ByteDance · Product Manager · 2021.03—2023.06" → ❌ Skip (no verbs, no results)
• "A Cultural Media Company　2023.7~2025.11　New Media-Operation Group" → ❌ Skip ("Operation" is the department name, not an action description)
• "An Internet Technology Company　2022.6~2023.6　Marketing Department-Brand Group" → ❌ Skip ("Brand" is the department name, not an action description)
• "XX University　2018.9~2022.6　Journalism and Communication-Bachelor" → ❌ Skip (educational entry, no action, no result)
• "Project Name: xxx Platform | Role: Leader | 2022.01—2022.06" → ❌ Skip (no verbs, no results)

• "During my tenure as a Product Manager at ByteDance, I led the launch of the xx project, increasing DAU by 40%" → ✅ Evaluate (contains verb + result)

• Whether a large number of passive verbs such as "responsible for", "participated in", "assisted" are used (minus points, recommended to change to active verbs)
• Whether there are obvious quantifiable but blank indicators (the tailor stage will insert

  [Please fill in: xxx]

  placeholder)

• Inform the user: "Okay, directly send me the new resume after revision (supports file / path / pasted text)."
• Stop execution and wait for the user to send the resume again
• After receiving, process in the same way as Step 2, overwrite and save

  resume.md

• Re-execute Step 2.5 (loop until the user chooses B)

• Inform the user: "Okay, continue."
• Execute Step 3

job-hunt-fetcher

• work_dir

  : <value of data_dir>

• run_id

  : <current run_id>

• screenshots

  : <batch of screenshots>

ls "<directory path>"

find "<directory>" -maxdepth 1 -type f \( -iname "*.png" -o -iname "*.jpg" -o -iname "*.jpeg" -o -iname "*.webp" -o -iname "*.jobs.json" \) | sort

• Images → Branch A (call fetcher)
• Each .jobs.json → Branch C (call import_jobs.py)

if command -v python3 >/dev/null 2>&1; then PYBIN=python3; \
elif command -v python >/dev/null 2>&1; then PYBIN=python; \
else echo "PYTHON_MISSING"; exit 1; fi

"$PYBIN" "$HOME/.claude/skills/job-hunt/import_jobs.py" "<data_dir>" "<json_path>"

• OK: Imported N jobs -> ...

  → Success, continue

• ERROR: ...

  → Inform the user "Failed to process .jobs.json: <reason>. Please check the file and resend." and wait again

• PYTHON_MISSING

  → Inform the user "Python 3 is required to process .jobs.json, please install and try again." and stop

• Scan all

  .md

  files under

  <data_dir>/.work/jd-pool/

  (exclude files ending with

  .analysis.md

  )
• Read the frontmatter of each file, filter files with

  status.analyzed: false

  , extract their

  id

  fields
• Exclude IDs that have been recorded as failed in

  state.json.stages.analysis_errors

job-hunt-analyzer

• work_dir

  : <absolute path>

• resume_path

  :

  <data_dir>/.work/resume.md

• jd_ids

  : <list of JD IDs to be analyzed>

• preferences

  :

  {"soft_preferences": {"prefer_industries": [], "avoid_industries": [], "prefer_company_size": []}, "ranking": {"match_weight": 1.0, "preference_weight": 0.0}}

• run_id

  : <current run_id>

state.json

phase

"analyzed"

<data_dir>/.work/resume.md

state.json

stages.tailored

job-hunt-tailor

• work_dir

  : <absolute path>

• resume_path

  :

  <data_dir>/.work/resume.md

• jd_ids

  : <complete sorted JD ID list>

• run_id

  : <current run_id>

state.json

phase

"tailored"

1. Use Bash tool: Detect Python, call

   build_html.py

   to generate shortlist.html
2. Use Bash tool: Update

   state.json

   's

   phase

   to

   "done"

3. Final Step: Output a short completion message in the chat (only contains HTML link + operation prompt, no longer output ranking MD overview, because the HTML view is for viewing these contents)

undefined

Fallback (common on Windows where only python exists, no python3)