SKILLEMALL.ai

AB prd-creator

Creates production-grade, internationally-standardized Product Requirements Documents (PRDs) for full-stack web/mobile projects, plus an execution-ready task breakdown so a coding agent (Claude Code, opencode CLI, etc.) can implement directly from it. Synthesizes ISO/IEC/IEEE 29148:2018, IEEE 830, Amazon's Working Backwards PR/FAQ, and Big Tech PRD conventions into one rigorous English .md deliverable. Use whenever the user asks to write/draft a PRD, product spec, SRS, feature spec, implementation plan, or "dokumen requirement/spesifikasi produk" — for any web, mobile, or full-stack system, even from a one-sentence idea. Also trigger to formalize an existing idea/backlog item into a proper requirements document, for a PRD "standar internasional"/"lengkap"/"seperti dibuat expert", or to prepare a project brief before handing off to Claude Code/opencode. Do NOT trigger for quick one-off feature descriptions the user wants kept short and informal.

ClawHub Agent Skills author: Anjasta Bagus Tarigan v1.0.2 MIT-0 5 files body ≈ 2 531 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 65/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

GeneratorSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
B
65/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Result and completion w 14
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: 5. 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 65/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Failures and branches. 4 branches
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2531 tokens
    • 100Running it twice. Mutating operations check current state
    • 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Description length 958: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 4 example trigger phrases
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 39 items
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: clean
    This skill is a documentation helper that creates PRD and task Markdown files, with no evidence of hidden code execution, credential use, or data exfiltration.
    LLM: benign (high) · VirusTotal: · 13 Jul 2026