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    🧭 Evidence-Bound Resume Builder

    3

    Prepare a role-specific resume and matching cover-letter draft from your permitted career facts, with excluded claims and shared provenance.

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    🧭 Evidence-Bound Resume Builder

    🧭 Evidence-Bound Resume Builder

    Example session with this skill installed

    Run the included synthetic practice.json fixture with python scripts/run.py fixtures/practice.json --output review. Prepare the resume and matching cover letter, keeping unsupported claims out of both.

    {
    "original_resume": "I built Python reporting tools for our weekly volunteer rota.\nI checked the rota against availability notes and documented the corrections for the coordinator.",

      "job_description": "Python reporting role",
      "sources": [
        {
          "id": "s1",
    
      "text": "I built Python reporting tools for our weekly volunteer rota.",
    
          "locator": "notes:line-2",
          "permitted": true
        },
        {
          "id": "s2",
    
      "text": "I checked the rota against availability notes and documented the corrections for the coordinator.",
    
          "locator": "volunteer-notes:4",
          "permitted": true
        }
      ],
      "claims": [
        {
          "id": "c1",
    
      "text": "I built Python reporting tools for our weekly volunteer rota.",
    
          "source_id": "s1",
          "requirement_ids": [
            "r1"
          ]
        },
        {
          "id": "c2",
    
      "text": "Increased revenue by 73%.",
    
          "source_id": "s1",
          "requirement_ids": [
            "r1"
          ]
        },
        {
          "id": "c3",
    
      "text": "I checked the rota against availability notes and documented the corrections for the coordinator.",
    
          "source_id": "s2",
          "requirement_ids": [
            "r1"
          ]
        }
      ],
      "requirements": [
        {
          "id": "r1",
          "text": "Python"
        },
        {
          "id": "r2",
          "text": "Budget leadership"
        }
      ],
      "application": {
        "role": "Reporting assistant",
        "company": "Example Community Centre",
        "job_locator": "supplied-job:1",
        "claim_ids": [
          "c1",
          "c2",
          "c3"
        ]
      }
    }
    
    • Read your context and instructions
    • Compiled the evidence-bound resume builder
    • Generated the data export

    Synthetic fixture: complete cover-letter-draft.txt

    Dear hiring team,

    I am applying for the Reporting assistant role at Example Community Centre.

    I built Python reporting tools for our weekly volunteer rota.

    I checked the rota against availability notes and documented the corrections for the coordinator.

    Thank you for considering my application.

    Other generated files: application-provenance.csv, application-review.md, candidate-questions.md, claim-provenance.csv, cover-letter-draft.md, cover-letter-draft.txt, findings.csv, manifest.json, original-resume.txt, report.md, requirement-coverage.csv, resume-draft.md, resume-draft.txt, summary.json.

    The planted 73% revenue claim is excluded. Review the source facts and job relevance before improving presentation and submitting yourself. No application was sent.

    evidence-bound-resume-builder.csv

    CSV · data export

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    For an applicant tailoring to a supplied role, prepare resume and cover-letter drafts from one permitted fact set so unsupported claims are excluded from both, with a shared provenance file.Prepare your next application or practice session using your own approved facts.Return to a saved packet without losing earlier work.

    About this skill

    Prepare a role-specific resume and matching cover-letter draft from your permitted career facts, with excluded claims and shared provenance. This downloadable skill helps the person work on their own application or practice session. It includes a local Python helper, synthetic worked example, input contract, executable tests and real output files. For an applicant tailoring to a supplied role, prepare resume and cover-letter drafts from one permitted fact set so unsupported claims are excluded from both, with a shared provenance file. Extractive source-unit assembly; candidate and agent improve presentation without inventing facts. No automatic career verification, ATS score, PDF resume designer or application submission. Role/company and fact relevance are supplied, not independently authenticated.

    Version 1.1.0. License: use and modify for your own work and internal organizational workflows; share resulting reports with authorized clients. Do not resell, redistribute, sublicense or publish the package or source as a competing download. See included LICENSE.txt for full approved terms.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
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      Download the ZIP

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    2. 2

      Unzip into your skills folder

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    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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    Verified clean 13 days ago

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    Listed13 days ago
    Updated11 days ago

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