SKILLEMALL.ai

AB rd-initiation-review

R&D project initiation pre-screen and proposal audit for go/no-go decisions, public novelty boundary review, innovation-point assessment, and evidence-backed project rating. Use when the user asks for project initiation pre-screening, initiation review, proposal review, R&D project evaluation, proposal-package review, novelty pre-screening, innovation-point review, project rating, or wants a formal review around a concrete project, proposal, or research-package material set — even if they only provide the proposal and do not explicitly say "review".

ClawHub Claude Code author: yuanzhian-patsnap v1.0.1 MIT-0 18 files body ≈ 4 018 tokens Open the sourceclawhub.ai analyzed 3 d ago

R&D project initiation pre-screen and proposal audit for go/no-go decisions, public novelty boundary review, innovation-point assessment, and evidence-backed…

As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, running it twice

AnalyzerData and analyticsAI 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%
84
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Running it twice w 4
30
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: 18. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "copyright"
    • note frontmatter-key unknown frontmatter key "provider"
    • note frontmatter-key unknown frontmatter key "deliverable-default"
    • note frontmatter-key unknown frontmatter key "fallback-policy"

    Process rating: all ten parameters 69/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 30Running it twice. 8 mutating operations with no state check
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4018 tokens
    • 85Steps. 165 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 12 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 555: enough signal without eating the budget
    • +4Structure: 37 headings
    • +3Step-by-step instructions: 165 items
    • +3Output format is stated explicitly
    • +4Reference files are cited in the instructions (7 of 7)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: clean
    This skill is a transparent R&D proposal review workflow that writes local evidence files and uses available research tools in ways that match its stated purpose.
    LLM: benign (high) · VirusTotal: · 13 Aug 2026