SKILLEMALL.ai

AC office-hours

YC Office Hours diagnostic — six forcing questions that expose demand reality, status quo, desperate specificity, narrowest wedge, observation, and future-fit. Adapted from Garry Tan's gstack office-hours skill. Use when asked to "brainstorm this", "I have an idea", "is this worth building", "office hours", "evaluate my startup", "诊断我的项目", "创业诊断", or when the user describes a new product idea and wants to know if it's worth pursuing.

ClawHub Agent Skills author: qianen6 v1.1.0 MIT-0 2 files body ≈ 3 014 tokens Open the sourceclawhub.ai analyzed 4 d ago

As a process C 60/100 · Has gaps — weak spots: inputs and preconditions, consistency, running it twice

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
C
60/100
Has gaps
Inputs and preconditions w 11
0
Running it twice w 4
30
Consistency w 8
40
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: 2. 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 60/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 15 mutating operations with no state check
    • 40Consistency. Frontmatter name (office-hours) differs from the folder (yc-office-hours)
    • 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 7 branches
    • 85Steps. 55 steps, 1 vague phrases
    • 100Execution cost. Instruction body is 3014 tokens
    • 100Progress reporting. Reports progress
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 437: enough signal without eating the budget
    • +4Structure: 24 headings
    • +3Step-by-step instructions: 55 items
    • +3Output format is stated explicitly
    • +4Has examples (2 code blocks)

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

    External checks

    ClawHub: clean
    This is a startup diagnostic skill that performs disclosed web research, limited project-context reading, and a bounded report write, with no evidence of hidden or malicious behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026