SKILLEMALL.ai

AC zh-project-proposal-writing

Use when the user needs to draft, revise, diagnose, shorten, expand, structure, finalize, or produce a deliverable Chinese project/grant proposal(中文项目申请书、基金申请书、科技计划申报书、可交付项目书), especially NSFC/国家自然科学基金、国家重点研发计划、上海市科委、杰青优青等人才类项目;handles guide interpretation, constraints matrix, title, abstract, rationale, scientific question or technical bottleneck, objectives, tasks, methods, roadmap, innovation, feasibility, budget, risk, compliance, attachments, expert-wisdom synthesis, review-style scoring, and final delivery as a Word .docx document.

ClawHub Agent Skills author: Jie Zhou v1.0.1 MIT-0 14 files body ≈ 1 530 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process C 59/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerWordSecurityInfrastructureOperations and projectstype 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
C
59/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 14. 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 59/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 45 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1530 tokens
    • 100Running it twice. No mutating operations
    • 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)
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 543: enough signal without eating the budget
    • +4Structure: 16 headings
    • +3Step-by-step instructions: 45 items
    • +4Reference files are cited in the instructions (8 of 8)

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

    External checks

    ClawHub: clean
    This is a coherent Chinese grant/proposal-writing skill with disclosed document generation and no executable code or hidden runtime behavior.
    LLM: benign (high) · VirusTotal: · 29 May 2026