SKILLEMALL.ai

AC spikecv-helper

Help AI Agents answer questions and execute tasks for SpikeCV, an ultra-high-speed spike camera vision framework. Use when the user asks about spike cameras, SpikeCV repository, spike dataset download, running vision task like tracking, reconstruction through spike vision, etc.

ClawHub Agent Skills author: LHS183019 v1.0.2 MIT-0 4 files body ≈ 2 197 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

Help AI Agents answer questions and execute tasks for SpikeCV, an ultra-high-speed spike camera vision framework.

As a process C 63/100 · Has gaps — weak spots: result and completion, failures and branches

ProcedureGitHubData and analyticsAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
88
Run on models
none yet
Process rating
C
63/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Tools and files w 18
60
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: 4. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note edit-residue the text marks something as outdated (lines 151, 152, 153, 154): check that old rules are not kept next to new ones — the full check reads the text for contradictions

    Process rating: all ten parameters 63/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 85Steps. 14 steps, 1 vague phrases
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2197 tokens
    • 100Running it twice. No mutating operations
    • 100Progress reporting. Reports progress

    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 278: enough signal without eating the budget
    • +4Structure: 11 headings
    • +3Step-by-step instructions: 14 items
    • +4Has examples (8 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 88.

    External checks

    ClawHub: clean
    This SpikeCV helper is a coherent documentation skill, but users should review the install and download commands before running them.
    LLM: benign (high) · VirusTotal: · 16 Sept 2026