SKILLEMALL.ai

BD game-dev-combat-animation

Build, fix and review character combat animations (melee strikes, bow shots, spell casts, skills, monster attacks, whole move sets) so they read like Diablo IV, Baldur's Gate 3 or Elden Ring and never stretch, lock, wring or break an arm, wrist or hand. A written standard with numbered rules, per-frame tests on the real skinned mesh, keys designed from upper-arm, forearm and blade intents, checks from every camera the player sees, two blind critics plus a blind A/B against the last release, and every critic claim verified against full-resolution frames and live-rig numbers. Use when creating or reworking any attack, skill or move set; when the user says arms, hands, wrists, elbows or weapons look stretched, weird, broken or wrong; when they ask for a standard, rules or tests for animations; or when they ask to score animations or get them to N out of 10.

MengTo/Skills Agent Skills author: MengTo MIT 27 files · 17 scripts body ≈ 1 753 tokens Open the sourcegithub.com↗ analyzed 3 d ago

Build, fix and review character combat animations (melee strikes, bow shots, spell casts, skills, monster attacks, whole move sets) so they read like Diablo…

As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerData and analyticstype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
49/100
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: 26. 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 49/100

    • 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
    • 30Running it twice. 6 mutating operations with no state check
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 47 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1753 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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)
    • +3Description length 866: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +4No input/output examples
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 47 items
    • +4Reference files are cited in the instructions (5 of 5)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.