Resume bullet editor

Skill nicholashidalgo/claude-skillforge/career/resume-bullet-editor

Install

npx -y skills add nicholashidalgo/claude-skillforge --skill resume-bullet-editor

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Edits existing resume bullets to remove banned language and add metrics without changing meaning.

SKILL.md

3.5 KB, as published. Nobody here has run it

resume-editor

Purpose: Take existing resume bullets and improve them: remove banned phrases, add or surface metrics, start with action verbs. Preserve all factual claims.

Input Schema

Field	Type	Required
`bullets`	string[]	yes - existing resume bullets
`context`	string	no - additional context for metric inference
`preserve_facts`	string[]	yes - must not change these
`tone`	string	yes

{
  "bullets": [
    "Responsible for managing the data pipeline",
    "Helped improve system reliability",
    "Strong communicator who worked with stakeholders"
  ],
  "context": "Senior Data Engineer at a fintech startup, 2021-2023",
  "preserve_facts": ["data pipeline", "fintech"],
  "tone": "direct"
}

Output Schema

{
  "edited_bullets": [
    {"original": "...", "revised": "...", "changes": ["removed 'responsible for'", "added action verb 'Owned'"]}
  ],
  "banned_phrases_removed": ["responsible for", "helped", "strong communicator"],
  "metric_warnings": ["bullet 2: no metric found - add a number before publishing"]
}

Prompt Flow

Pass 1: For each bullet: flag banned phrases -> rewrite starting with action verb -> inject metric if known -> preserve preserve_facts. Pass 2: Audit for remaining AI tells. Flag bullets with no metric as warnings (do not fabricate metrics).

Examples

Short

Before: "Responsible for managing the data pipeline." After: "Owned and maintained the Airflow-based data pipeline processing 500GB nightly."

Medium

Before: "Helped improve system reliability and worked with the on-call team." After: "Reduced mean time to recovery from 45 min to 12 min by documenting the top 8 incident runbooks."

Long

Before: "Results-driven professional responsible for driving cross-functional collaboration to achieve business outcomes." After: "Led quarterly roadmap reviews with product, engineering, and sales (12 stakeholders); 9 of 11 Q3 commitments shipped on time."

Unit Tests

# tests/skills/test_resume_editor.py
from resume_banned import flag_banned_phrases

EDITED = [
    "Owned and maintained the Airflow-based data pipeline processing 500GB nightly.",
    "Reduced MTTR from 45 min to 12 min by documenting 8 incident runbooks.",
]

def test_edited_bullets_no_banned_phrases():
    for b in EDITED:
        assert flag_banned_phrases(b) == [], f"Banned phrase remains: {b}"

def test_edited_bullets_start_with_verb():
    action_verbs = {"owned","reduced","built","cut","shipped","led","wrote","launched","designed","managed","created"}
    for b in EDITED:
        first_word = b.split()[0].lower().rstrip(".,")
        assert first_word in action_verbs, f"Bullet doesn't start with action verb: {b}"

def test_metric_warning_issued_for_vague_bullet():
    # resume-editor should flag bullets with no metric, not fabricate one
    from resume_editor import edit_bullets
    result = edit_bullets(["Strong communicator who worked with stakeholders."], preserve_facts=[])
    assert any("metric" in w.lower() for w in result.get("metric_warnings", [])), \
        "Expected metric warning for vague bullet"