SKILLEMALL.ai
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AF cv-builder

Creates professional CVs with permanent URLs at talent.de. Supports PDF export, multiple templates, 4 skill types, and human-in-the-loop review. Free API for AI agents — basic use without API key, full features with Access-ID. Use when the user wants to create, build, or generate a CV or resume.

modbender/skill-library-mcp Agent Skills author: modbender MIT 4 files body ≈ 2 477 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Creates professional CVs with permanent URLs at talent.de. Supports PDF export, multiple templates, 4 skill types, and human-in-the-loop review. Free API for…

As a process F 44/100 · Will not run — References files that are not bundled: review_url, ../shared/access.md, ../shared/errors.md

GeneratorPeople and hiringtype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
75
Run on models
none yet
Process rating
F
44/100
Will not run
References files that are not bundled: review_url, ../shared/access.md, ../shared/errors.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
  • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

Guard findings · 0

✓ No critical or high findings

Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: review_url
  • warning missing-ref reference to a missing file: ../shared/access.md
  • warning missing-ref reference to a missing file: ../shared/errors.md
  • warning missing-ref reference to a missing file: ../shared/privacy.md
  • note frontmatter-key unknown frontmatter key "homepage"
  • note frontmatter-key unknown frontmatter key "env_vars"

Process rating: all ten parameters 44/100

Will not run. References files that are not bundled: review_url, ../shared/access.md, ../shared/errors.md
  • 0Tools and files. 4 referenced file(s) missing: review_url, ../shared/access.md, ../shared/errors.md
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 30Running it twice. 9 mutating operations with no state check
  • 55Failures and branches. 1 branches
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 29 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2477 tokens
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 11 top-level sections: this looks like several domains in one skill

Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

Quality signals

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 296: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 29 items
  • +4Has examples (11 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.