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AC hiring-manager-deep-dive

Prepares for hiring manager rounds at Staff+ (L6+) level — scope of impact, influence without authority, ambiguity navigation, mentorship, strategic thinking. Use when practicing HM rounds or calibrating story depth for target level. Activate on "hiring manager round", "HM screen", "staff level", "scope of impact". NOT for coding interviews, system design, behavioral/values rounds, or resume writing.

curiositech/some_claude_skills Agent Skills author: curiositech 4 files body ≈ 3 215 tokens Open the sourcegithub.com↗ analyzed 39 min ago

Prepares for hiring manager rounds at Staff+ (L6+) level — scope of impact, influence without authority, ambiguity navigation, mentorship, strategic thinking.

As a process C 64/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice

GeneratorPeople and hiringtype 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
99/100
safety, quality, tests
Safety 60%
100
Quality 40%
97
Run on models
none yet
Process rating
C
64/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
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: 4. 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 64/100

    • 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. 3 mutating operations with no state check
    • 50When it triggers. No condition that starts the skill
    • 100Tools and files. Tools declared in frontmatter
    • 100Steps. 41 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3215 tokens

    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

    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 403: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 41 items
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.