CD mamba-architecture
State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.
State-space model with O(n) complexity vs Transformers' O(n²).
As a process D 38/100 · Unfinished process — References files that are not bundled: references/selective-ssm.md, references/mamba2-details.md, references/performance.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/selective-ssm.md - warning
missing-refreference to a missing file: references/mamba2-details.md - warning
missing-refreference to a missing file: references/performance.md - note
frontmatter-keyunknown frontmatter key "dependencies"
Process rating: all ten parameters 38/100
- 0Tools and files. 3 referenced file(s) missing: references/selective-ssm.md, references/mamba2-details.md, references/performance.md
- 0Result and completion. Does not say what the result is
- 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
- 40Consistency. Frontmatter name (mamba-architecture) differs from the folder (mamba)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 43 steps
- 100Execution cost. Instruction body is 1696 tokens
- 100Running it twice. No mutating operations
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
- -43 reference files, but SKILL.md never points to them: the model will not open them
- +2Single-language instructions
- +3Description length 256: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 43 items
- +4Has examples (11 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.