BC nom
Fetch recent GitHub activity from the Nom feed
As a process C 60/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice
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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
name-missingSKILL.md: frontmatter has no `name` - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 60/100
- 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. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 60Result and completion. Output format stated, no completion criterion
- 85Steps. 19 steps, 1 vague phrases
- 100Tools and files. Tools declared in frontmatter
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 592 tokens
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 46: 120–800 characters recommended
- +4Structure: 0 headings, hard to scan
- +1No license
- +2Single-language instructions
- +3Step-by-step instructions: 19 items
- +3Output format is stated explicitly
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 38.
External checks
ClawHub: clean
This skill is an instruction-only GitHub activity fetcher that uses a disclosed web endpoint and does not request local access, credentials, persistence, or shell execution.
LLM: benign (high) · VirusTotal: benign · 28 May 2026