SKILLEMALL.ai

BC autosolutions-npd-validator

Run a full NPD validation pipeline on a product concept. Orchestrates 8 specialized subagents (Research Coordinator, 5 Independent Evaluators, Devil's Advocate, Consensus Director) to produce an evidence-based GO / CONDITIONAL GO / REVISIT / NO-GO recommendation. Use when someone asks to validate a product idea, assess market fit, or evaluate whether a product should be launched.

ClawHub Agent Skills author: Didac v1.0.1 MIT-0 3 files body ≈ 3 455 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
79/100
safety, quality, tests
Safety 60%
95
Quality 40%
54
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

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 · 1

    ✓ No critical or high findings

    Medium and low: 1
    • medium Broad scope meta-broad-allowed-tools SKILL.md:1
      Broad tool permissions pre-approved: Bash
      allowed-tools: Read Write Edit Bash WebSearch SubAgent

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • error name-missing SKILL.md: frontmatter has no `name`

    Process rating: all ten parameters 60/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 20When it triggers. No condition that starts the skill
    • 70Failures and branches. 7 branches
    • 85Steps. 73 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 3455 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress

    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
    • +1No license
    • +2Single-language instructions
    • +3Description length 382: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 73 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 54.

    External checks

    ClawHub: clean
    This is an instruction-only product-validation skill whose local file writing, web research, and subagent orchestration are disclosed and aligned with its purpose.
    LLM: benign (high) · VirusTotal: · 29 May 2026