SKILLEMALL.ai
GitHub ↗ RU Sign in

AB linkedin-story-interviewer

Interviews a person to surface what they actually have to say, and keeps the answers in a local story bank file that later LinkedIn drafts draw on. Use when someone has never posted, when drafts keep coming out generic, or when the story bank is thin or stale.

borghei/Claude-Skills Agent Skills author: borghei 10 files · 2 scripts body ≈ 3 739 tokens Open the sourcegithub.com↗ analyzed 7 h ago

Interviews a person to surface what they actually have to say, and keeps the answers in a local story bank file that later LinkedIn drafts draw on.

As a process B 67/100 · Nearly there — weak spots: result and completion

ProcedureSoftware developmentData and analyticsAI and agentstype and topics are labelled automatically from the skill text
Runs in: 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) OpenClaw Goose OpenCode
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
67/100
Nearly there
Result and completion w 14
0
When it triggers w 12
50
Tools and files w 18
60
the three weakest of ten parameters · all ten

How to improve

    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: 10. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 67/100

    • 0Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 70Failures and branches. 4 branches
    • 100Steps. 43 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3739 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 260: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 43 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 2 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.