SKILLEMALL.ai

AC oem-rfq-assistant

Turn an inbound B2B manufacturing RFQ / sourcing inquiry into three artifacts: a structured spec sheet, a missing-information clarification checklist, and a professional English reply draft — WITHOUT inventing prices, MOQs, lead times, certifications, stock or test data. Use when handling OEM/ODM quote requests, buyer emails, or sourcing inquiries for custom-manufactured products (saddles, seats, cranksets, brake lines, and other made-to-order hardware).

ClawHub Agent Skills author: fly0pants v1.0.0 MIT-0 10 files body ≈ 1 484 tokens Open the sourceclawhub.ai analyzed 2 d ago

Turn an inbound B2B manufacturing RFQ / sourcing inquiry into three artifacts: a structured spec sheet, a missing-information clarification checklist, and a…

As a process C 56/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

ProcedureWhatsAppSales and CRMManufacturingtype and topics are labelled automatically from the skill text
JSON
Technical rating
A
98/100
safety, quality, tests
Safety 60%
100
Quality 40%
95
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
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: 10. 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 56/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 4 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) 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
    • 85Steps. 35 steps, 1 vague phrases
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1484 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

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +2Single-language instructions
    • +3Description length 458: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 35 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 95.

    External checks

    ClawHub: clean
    This skill is a straightforward RFQ drafting assistant with a local helper script, and its handling of buyer inquiry text fits its stated purpose.
    LLM: benign (high) · VirusTotal: · 19 Aug 2026