tamar-resume-tailor

# Tamar Resume Tailoring Use the `tamar` CLI to tailor resumes for specific job applications via the Tamar API. ## Triggers Activate when the user says anything like: - "tailor my resume" - "customize my resume for" - "help me apply for this job" - "make a resume for this role" - "adapt my resume" - "target my resume at" ## Prerequisites - The `tamar` CLI must be installed by the user before using this skill: `npm install -g tamar-cli` - An API key must be configured. Verify by running `tamar status`. If it fails with "No API key configured", ask the user to run `tamar auth --key <their-key>` (keys are obtained from https://ask-tamar.com → Profile → API Keys) - Do NOT read or inspect `~/.tamarrc` directly — use `tamar status` to check auth ## Pipeline ### 1. Check if the user has an experience profile ```bash tamar profile ``` Shows existing profiles with name, role, seniority, skills, and enrichment depth. If a profile exists, use its ID with `tamar tailor --profile <id>` for higher-quality output. If none exists, proceed to step 2. ### 2. Ensure user has a resume uploaded If the user has a resume file and hasn't uploaded one yet: ```bash tamar upload <resume-file> ``` ### 3. Get the job description Ask the user for the job description. It can be: - A URL (LinkedIn, company careers page, etc.) - A file path — read the file content first - Pasted text ### 4. Tailor the resume **IMPORTANT — Input safety:** Never interpolate user-provided strings directly into shell commands. Always write job descriptions or multi-word arguments to a temporary file and pass the file path, or use the `--` separator and single-quote the argument. This prevents shell injection from malicious input. ```bash # Safe: write JD to a temp file, pass the file echo '<job description text>' > /tmp/jd.txt tamar tailor --job /tmp/jd.txt # Safe: single-quote the argument to prevent shell expansion tamar tailor --job 'https://example.com/jobs/12345' ``` If the user also provides a resume file and hasn't uploaded before: ```bash tamar tailor --job /tmp/jd.txt --resume '<resume-file>' ``` ### 5. Review the output The command returns JSON with: - `id` — the generated resume ID (stored for later commands) - `quality` — `"enriched"` (has profile) or `"basic"` (resume-only) - `analysis` — job match analysis - `changes` — list of changes made Present the analysis summary conversationally. Highlight key matches and gaps. ### 6. Handle feedback If the user wants changes: Write the feedback to a temp file to avoid shell injection: ```bash echo '<feedback text>' > /tmp/feedback.txt tamar feedback "$(cat /tmp/feedback.txt)" ``` Or for a specific resume: ```bash tamar feedback "$(cat /tmp/feedback.txt)" --id '<resume-id>' ``` ### 7. Download the result ```bash tamar download # PDF (default) tamar download --format json # structured JSON ``` The PDF is saved to the current directory. Tell the user the file path. ## Error Handling | Error | Action | |-------|--------| | `No API key configured` | Guide user to run `tamar auth --key <key>` | | `401 Invalid or expired` | Prompt to re-run `tamar auth` with a new key | | `422 Could not parse URL` | Site blocks scraping (common with LinkedIn). Paste the JD text instead | | `429 Rate limited` | Tell user to wait and retry | | `402 Plan limit reached` | Direct to https://ask-tamar.com for upgrade | | Network error / timeout | Check connection. AI calls can take 15–60s — ensure client timeout is ≥120s | ## Quality Notes - **Enriched** quality (user has an experience profile — check via `tamar profile`) = higher quality tailoring - **Basic** quality (resume-only, no profile) = still useful but less nuanced - If user has no profile, suggest building one at https://ask-tamar.com via the interactive Q&A, or use the enrichment API flow ## Example Interaction ``` User: Can you tailor my resume for this job? https://linkedin.com/jobs/12345 Agent: Let me tailor your resume for that role. [runs: tamar tailor --job 'https://linkedin.com/jobs/12345'] Agent: Done! Here's what I found: - Quality: enriched (used your experience profile) - Key alignments: Python, data pipelines, team leadership - Adjusted: Reframed your experience to emphasize data platform work - Gaps: Kubernetes — no production experience listed Want me to tweak anything? I can also download the PDF for you. ```