BB convex-backend
Store secrets, long-term memory, daily logs, and anything custom in your Convex backend instead of local files
As a process B 72/100 · Nearly there — weak spots: result and completion, consistency, running it twice
ProcedureSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
The same skill appears in 1 more place: ClawHub
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 15. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "requires"
Process rating: all ten parameters 72/100
- 0Result and completion. Does not say what the result is
- 30Running it twice. 30 mutating operations with no state check
- 40Consistency. Frontmatter name (convex-backend) differs from the folder (launchthatbot-convex-backend)
- 50When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 65 steps
- 100Inputs and preconditions. Inputs and preconditions are listed
- 100Failures and branches. 13 branches, has a failure section
- 100Execution cost. Instruction body is 3020 tokens
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 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)
- +3Description length 110: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +4Structure: 21 headings
- +3Step-by-step instructions: 65 items
- +4Has examples (12 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.
External checks
ClawHub: clean
This skill performs sensitive Convex-backed secret and memory storage, but the behavior is disclosed, purpose-aligned, and user-controlled enough to remain benign.
LLM: benign (high) · VirusTotal: benign · 28 May 2026