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Add jobstead skill#2285

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Add jobstead skill#2285
adibas03 wants to merge 1 commit into
github:mainfrom
adibas03:add-jobstead-skill

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Persistent, session-spanning job-search companion: fit-checks a posting against a stored applicant profile, flags scam patterns, and tailors a resume/cover letter grounded in the person's real background rather than generic one-shot advice. Profile, application tracker, and accumulated lessons persist across sessions in references/.

Claude-Session: https://claude.ai/code/session_01Q5CnBdJyAAY3g11qj7i8ha

Pull Request Checklist

  • I have read and followed the CONTRIBUTING.md guidelines.
  • I have read and followed the Guidance for submissions involving paid services (not applicable — no paid services involved).
  • My contribution adds a new skill in the correct directory (skills/jobstead/).
  • The file follows the required naming convention (folder name matches name in frontmatter, lowercase-hyphenated).
  • The content is clearly structured and follows the example format.
  • I have tested the skill's triggering behavior extensively (see Additional Notes).
  • I have run npm start and verified that the generated docs (docs/README.skills.md) are up to date.
  • I am targeting the main branch for this pull request.

Description

Adds jobstead, a persistent, session-spanning job-search companion skill. Unlike a one-shot task helper, it grounds every fit-check and story in accumulated state that persists across sessions:

  • references/profile.md — the applicant's background, work authorization, target roles, and constraints (ships blank; the skill asks for a resume on first use and fills it in)
  • references/tracker.md — an append-only application tracker (applied/rejected/offered/deferred, etc.)
  • references/lessons.md — accumulated, identity-free patterns learned across the search (seeded with a starter playbook covering visa/sponsorship signals, salary-floor plausibility checks, ATS-tool cost/benefit, and cover-letter framing)
  • references/log.md — a per-session activity audit

Core capabilities: fit-checking a posting against the stored profile (not generic advice), catching scam patterns in postings/recruiter messages, and building a story-grounded, ATS-optimized resume/cover letter tied to a specific role.

Relationship to technical-job-search

This repo already has a technical-job-search skill, which is explicitly one-shot/stateless per task (JD analysis, CV tailoring, cover letter, offer evaluation, follow-up email — no persistence across sessions). jobstead is a different, complementary tool: everything it does is grounded in a profile/tracker/lessons state that accumulates over the whole job search rather than being re-derived each time, and it explicitly covers scam-detection as a first-class use case.


Type of Contribution

  • New skill file.

Additional Notes

The trigger description was validated with an extensive eval methodology (sequential nested-session testing across a 60-query set of should-trigger/should-not-trigger phrasings, with full transcript capture rather than pass/fail booleans): 86% recall, ~100% precision on fair, well-formed queries. Happy to share the eval harness/results if useful for review.


By submitting this pull request, I confirm that my contribution abides by the Code of Conduct and will be licensed under the MIT License.

Persistent, session-spanning job-search companion: fit-checks a posting
against a stored applicant profile, flags scam patterns, and tailors a
resume/cover letter grounded in the person's real background rather than
generic one-shot advice. Profile, application tracker, and accumulated
lessons persist across sessions in references/.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Q5CnBdJyAAY3g11qj7i8ha
@adibas03 adibas03 requested a review from aaronpowell as a code owner July 13, 2026 13:47
@github-actions github-actions Bot added new-submission PR adds at least one new contribution skills PR touches skills labels Jul 13, 2026
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🔒 PR Risk Scan Results

Scanned 6 changed file(s).

Severity Count
🔴 High 0
🟠 Medium 1
ℹ️ Info 0
Severity Rule File Line Match
🟠 package-exec-command docs/README.skills.md 31 | [acreadiness-assess](../skills/acreadiness-assess/SKILL.md)&lt;br /&gt;`gh skills install github/awesome-copilot acreadiness-assess` | Run the AgentRC readiness assessment on the curre

This is an automated soft-gate report. Findings indicate review targets and do not block merge by themselves.

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🔍 Vally Lint Results

✅ All checks passed

Scope Checked
Skills 1
Agents 0
Total 1
Severity Count
❌ Errors 0
⚠️ Warnings 0
ℹ️ Advisories 0

Summary

Level Finding
ℹ️ npm warn EBADENGINE Unsupported engine {
ℹ️ npm warn EBADENGINE package: 'commander@15.0.0',
ℹ️ npm warn EBADENGINE required: { node: '>=22.12.0' },
ℹ️ npm warn EBADENGINE current: { node: 'v20.20.2', npm: '10.8.2' }
ℹ️ npm warn EBADENGINE }
ℹ️ npm warn deprecated prebuild-install@7.1.3: No longer maintained. Please contact the author of the relevant native addon; alternatives are available.
ℹ️ ✅ jobstead (2/2 checks passed)
ℹ️ ✓ [spec-compliance] All 1 skill(s) are spec-compliant.
ℹ️ ✓ spec-compliance: All spec checks passed.
ℹ️ ✓ [valid-refs] All file references across 1 skill(s) are valid.
Full linter output
### Linting skills/jobstead
npm warn EBADENGINE Unsupported engine {
npm warn EBADENGINE   package: 'commander@15.0.0',
npm warn EBADENGINE   required: { node: '>=22.12.0' },
npm warn EBADENGINE   current: { node: 'v20.20.2', npm: '10.8.2' }
npm warn EBADENGINE }
npm warn deprecated prebuild-install@7.1.3: No longer maintained. Please contact the author of the relevant native addon; alternatives are available.
✅ jobstead (2/2 checks passed)
    ✓ [spec-compliance] All 1 skill(s) are spec-compliant.
        ✓ spec-compliance: All spec checks passed.
    ✓ [valid-refs] All file references across 1 skill(s) are valid.
        ✓ valid-refs: All file references resolve to existing files within the skill directory.

1 skill(s) linted, 1 passed

@aaronpowell

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This doesn't really fit with awesome copilot at the moment.

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3 participants