tech-resume-optimizer
Optimize resumes for software engineering, PM, and technical roles
32
24%
Does it follow best practices?
Impact
—
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/tech-resume-optimizer/SKILL.mdQuality
Discovery
22%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description is too terse and vague to effectively guide skill selection. It names a domain (resume optimization for tech roles) but fails to specify concrete actions or provide explicit trigger conditions. Without a 'Use when...' clause and with only a single generic verb, Claude would struggle to reliably select this skill over other writing or career-related skills.
Suggestions
Add a 'Use when...' clause with trigger terms like 'resume', 'CV', 'job application', 'ATS optimization', 'career', or 'applying for a role'.
List specific concrete actions such as 'Rewrites bullet points with quantified achievements, tailors keywords for ATS systems, restructures resume sections for target roles, and suggests improvements for technical resumes.'
Include common user phrasing variations like 'review my resume', 'help with my CV', 'tailor resume for a job posting', or 'improve my job application'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses the single vague verb 'optimize' without specifying concrete actions like rewriting bullet points, tailoring keywords, restructuring sections, or quantifying achievements. It names a domain (resumes for tech roles) but lacks actionable detail. | 1 / 3 |
Completeness | It partially addresses 'what' (optimize resumes) but provides no explicit 'when' clause or trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also weak, so this scores a 1. | 1 / 3 |
Trigger Term Quality | Includes some natural keywords users might say ('resumes', 'software engineering', 'PM', 'technical roles'), but misses common variations like 'CV', 'job application', 'ATS', 'cover letter', 'career', or 'tailor resume'. | 2 / 3 |
Distinctiveness Conflict Risk | The focus on resumes for technical roles provides some specificity, but 'optimize' is vague enough that it could overlap with general writing improvement or career coaching skills. The mention of specific role types (software engineering, PM) helps somewhat. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
27%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like a comprehensive career guide than a focused instruction set for Claude. While it contains useful concrete examples (especially the before/after bullet transformations and output format), it is severely bloated with general knowledge Claude already possesses, exhaustive technology lists, and career advice tangential to the core task of resume optimization. The lack of any progressive disclosure or bundle structure means all content competes for context window space.
Suggestions
Cut at least 60% of content: remove technology enumeration lists, general career advice (interview prep, GitHub profile tips), and explanations of what recruiters look for — Claude already knows these things.
Extract role-specific examples (SWE, Data Engineer, DevOps, PM) into a separate EXAMPLES.md file and reference it from the main skill.
Add an explicit step-by-step workflow: 1) Identify target role type, 2) Extract and categorize existing skills, 3) Transform each bullet using the formula, 4) Validate ATS keyword coverage, 5) Generate output in template format.
Add validation checkpoints such as 'verify every technology in Skills section appears in at least one experience bullet' and 'confirm metrics are included in 70%+ of bullets.'
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~300+ lines. Explains concepts Claude already knows (what tech recruiters look for, what GitHub READMEs should include, interview prep advice). Lists every possible database, framework, and cloud tool. Much of this is general career advice, not actionable skill instructions. The skill could be reduced to ~30% of its size without losing useful guidance. | 1 / 3 |
Actionability | Provides concrete before/after examples of weak vs strong bullets and a clear output format template, which is genuinely useful. However, much of the content is descriptive lists (what to include/exclude) rather than executable transformation steps. The output format section is the strongest actionable element. | 2 / 3 |
Workflow Clarity | The output format section provides a clear structure for the optimization process, and the bullet formula gives a concrete pattern. However, there's no explicit step-by-step workflow for how to analyze and transform a resume — no validation checkpoints like 'verify all claimed skills appear in experience bullets' or 'check ATS keyword coverage against job description.' | 2 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files. All content — role-specific examples, GitHub tips, education formatting, ATS guidance — is inlined. Content like role-specific bullet examples, project formatting, and education section guidance could easily be split into separate reference files to keep the main skill lean. | 1 / 3 |
Total | 6 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- paramchoudhary/resumeskills
- Commit
24c6edc
- Reviewed
Table of Contents
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