SKILLEMALL.ai

BC update-docs-from-commits

Scan recent git commits for changes that affect user-facing behavior, then draft or update the corresponding documentation pages. Use when docs have fallen behind code changes, after a batch of features lands, or when preparing a release. Trigger keywords - update docs, draft docs, docs from commits, sync docs, catch up docs, doc debt, docs behind, docs drift.

NVIDIA/openshell Agent Skills author: NVIDIA Apache-2.0 1 file body ≈ 2 285 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Scan recent git commits for changes that affect user-facing behavior, then draft or update the corresponding documentation pages.

As a process C 61/100 · Has gaps — weak spots: result and completion, consistency

GeneratorSoftware developmentWriting and documentstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
C
61/100
Has gaps
Result and completion w 14
0
Consistency w 8
40
When it triggers w 12
50
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: 1. 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 61/100

    • 0Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (update-docs-from-commits) differs from the folder (update-docs)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 60Failures and branches. 2 branches
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 52 steps
    • 100Execution cost. Instruction body is 2285 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • low 11 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
    • +1No license
    • +2Single-language instructions
    • +3Description length 362: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 52 items
    • +4Has examples (7 code blocks)

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