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claude-resume-kit/.claude/skills/setup-extract/SKILL.md
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Akhil Reddy Peeketi c51b49882f Initial release — claude-resume-kit v1.0
Complete AI-assisted resume/CV generation framework:
- 6 Claude Code skills (setup-extract, setup-build-kb, make-resume, make-cl, edit-resume, critique)
- LaTeX templates (resume, CV, cover letter) with .cls class files
- 6 reference docs (shared_ops, resume_reference, cl_reference, critical_rules, session_file_template, critique_framework)
- Fictional Dr. Jordan Chen examples (extraction, experience, bundle, config, session, JD)
- Knowledge base scaffolding and config template
- README with setup guide and workflow documentation
2026-03-09 02:42:10 -06:00

6.7 KiB

description, user-invocable
description user-invocable
Extract structured information from research papers, PDFs, or code into knowledge base extractions true

/setup-extract

User input: $ARGUMENTS

Parse $ARGUMENTS:

  • File path to a paper (e.g., papers/Smith2024_catalyst.pdf, papers/project_report.tex) → read that file
  • Multiple paths separated by spaces → batch mode (process each sequentially)
  • Empty → ask the user for the paper path or paste content

Startup

  1. Read CLAUDE.md — check KB Corrections Log for known issues
  2. Read config.md — load Personal Info (to identify user's author position), Provenance Flags
  3. Read knowledge_base/extractions/_INVENTORY.md — see what's already extracted, avoid duplicates

If the paper is already in the inventory:

  • Show the existing extraction path
  • Ask: "This paper is already extracted. Re-extract (overwrite) or skip?"
  • Wait for user response before proceeding

Phase 1: Read & Understand the Paper

Read the paper using the appropriate method:

  • PDF files: Use the Read tool (supports PDF reading)
  • .tex source: Read directly — often has more detail than the compiled PDF
  • If both exist: Prefer .tex for content extraction, use PDF for figures/tables

While reading, collect:

  1. Full title, all authors, year, journal/venue, DOI (if available)
  2. The user's position in the author list (first, co-first, second, middle, last, corresponding)
  3. Publication status (check config.md Provenance Flags first, then infer: published / under review / draft / internal)
  4. All computational methods, experimental techniques, software, and frameworks mentioned
  5. Quantitative results — speedups, accuracies, efficiencies, improvements over baselines
  6. Novelty claims — "first-ever", "new framework", "novel approach", etc.
  7. Collaboration indicators — other groups, institutions, shared resources
  8. Funding acknowledgments

Progress: "Reading paper... [title] by [first author] et al., [year]"


Phase 2: Clarify User's Role

If the user's contribution is not obvious from the paper (common for multi-author work), ask:

Questions to ask (skip any that are already clear from the paper):

  1. "What was your specific contribution? (e.g., all computational work, specific analysis, code development)"
  2. "Did you develop any tools, methods, or code used in this paper?"
  3. "Were there other groups or institutions involved? What was your group's role?"
  4. "Any quantitative results you can personally claim? (e.g., 'I ran all the simulations')"
  5. "Is there anything in this paper that should NOT appear on your resume? (e.g., collaborator's experimental data)"

>>>>>> MANDATORY STOP — DO NOT PROCEED <<<<<<

Present your understanding of the paper and ask the clarifying questions above. You MUST wait for the user's explicit text response before continuing.


Phase 3: Write Extraction

Create the extraction file at knowledge_base/extractions/<AuthorYear_short_descriptor>.md

Naming convention: <FirstAuthorLastName><Year><2-3_word_descriptor>.md

  • Examples: Smith2024_protein_stability.md, Chen2023_binding_affinity.md
  • If the user is first author: use their last name
  • Normalize to lowercase with underscores

Extraction format:

# [Full Paper Title]

## Metadata
- **Authors:** [author list — highlight user's name with bold]
- **Year:** [year]
- **Journal:** [journal/venue or "unpublished"/"internal"/"under review at X"]
- **DOI:** [DOI or "N/A"]
- **User's role:** [first author / co-first / contributing / corresponding]
- **Status:** [published | under review | draft | internal]

## Methods & Tools
- **Computational methods:** [e.g., MD, ML, FEA, CFD, etc. — be specific about methods, force fields, etc.]
- **Software/frameworks:** [e.g., GROMACS, PyTorch, ABAQUS, custom code, etc.]
- **Hardware/HPC:** [if mentioned — clusters, GPU resources, etc.]
- **Key techniques:** [specific methodological details that map to resume skills]

## Key Results
[Number each result. Include quantitative metrics wherever possible.]
1. [Result with numbers — e.g., "Achieved 5,000x speedup over brute-force screening"]
2. [Result — e.g., "Screened 8,500 variants, identified 7 top candidates"]
3. [...]

## Novelty Claims
[What's genuinely new — be precise, avoid overclaiming]
- [e.g., "First application of framework X to system Y"]
- [e.g., "New method combining A and B — no prior work exists"]

## Collaboration & Scope
- **Other groups:** [institutions, PIs involved]
- **User's specific contribution:** [from Phase 2 clarification]
- **Shared vs. sole work:** [what the user did alone vs. with others]

## Provenance Notes
- **Publication status:** [matches config.md if listed there]
- **Safe to claim:** [what the user can put on a resume without hedging]
- **Needs hedging:** [claims that require "contributed to" or "supported" framing]
- **Do NOT claim:** [results from collaborators, claims that would be overclaiming]

## Resume Bullet Seeds
[3-5 draft bullets in STAR format. These are seeds, not final text.]
[Use full-ownership verbs only for sole-contributor work. Hedge for shared work.]
1. [Action verb] + [what was done] + [quantitative result/impact]
2. [Action verb] + [method/tool developed] + [what it enabled]
3. [Action verb] + [scope — e.g., "across N systems"] + [outcome]
4. [Optional: collaboration-framed bullet]
5. [Optional: tool/infrastructure bullet]

Save the file. Show the user the complete extraction.

Progress: "Writing extraction for [short title]... [N] results identified, [M] bullet seeds drafted"


Phase 4: Update Inventory

Read and update knowledge_base/extractions/_INVENTORY.md.

Add a row to the inventory table:

| [filename] | [short title] | [user's role] | [status] | [primary methods] | [date extracted] |

Present the updated inventory entry to the user.


Phase 5: Next Steps

After extraction is complete, present:

  1. Extraction summary: [N] methods, [M] quantitative results, [K] bullet seeds
  2. Provenance flags: Any items that need special handling
  3. Suggested next action:
    • If more papers to extract: "Run /setup-extract [next paper path]"
    • If all papers done: "Run /setup-build-kb to synthesize extractions into experience files and bundles"

>>>>>> MANDATORY STOP <<<<<<

Present extraction summary. Wait for user feedback or next paper. You MUST wait for the user's explicit text response before continuing.


Batch Mode

If $ARGUMENTS contains multiple file paths:

  1. Process each paper through Phases 1-4 sequentially
  2. Ask Phase 2 clarifying questions for ALL papers at once (grouped) before writing any extractions
  3. After all extractions: present combined inventory update and summary
  4. Single STOP at the end (not per paper)