SKILLEMALL.ai

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Low-level docx format tool for AI document review. Three operations: (1) read docx → output compact Markdown or JSON; (2) apply edits JSON back to docx (tracked revisions and comments); (3) finalize (accept revisions, remove comments). Markdown output saves tokens vs full JSON. Use when raw .docx read/write is needed. For full contract review workflow, use contract-review-workflow which invokes this tool.

modbender/skill-library-mcp Agent Skills author: modbender MIT 9 files body ≈ 954 tokens Open the sourcegithub.com analyzed 34 h ago

Low-level docx format tool for AI document review.

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerWordInfrastructureAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
D
43/100
Unfinished process
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: 9. 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 43/100

    • 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
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 6 mutating operations with no state check
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 17 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 954 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)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +3Description length 408: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 17 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 3 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.