BB open-websearch
Single entry skill for open-websearch setup and focused live retrieval, preferring local CLI/daemon paths while remaining compatible with workspace-exposed MCP tools.
As a process B 66/100 · Nearly there — weak spots: result and completion, when it triggers, consistency
IntegrationAI and agentsInfrastructuretype and topics are labelled automatically from the skill text
This is a copy of a skill from another catalog; the rating counts the canonical one: open-websearch (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: 5. 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 "version_note"
Process rating: all ten parameters 66/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (open-websearch) differs from the folder (openwebsearch)
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Tools and files. Tools declared in frontmatter
- 100Steps. 88 steps
- 100Failures and branches. 18 branches, has a failure section
- 100Execution cost. Instruction body is 2934 tokens
- 100Running it twice. No mutating operations
- low 10 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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 166: enough signal without eating the budget
- +4Structure: 11 headings
- +3Step-by-step instructions: 88 items
- +4Reference files are cited in the instructions (3 of 3)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.
External checks
ClawHub: clean
This skill is a transparent web-search setup and retrieval guide, with no executable payload and clear prompts before higher-impact setup actions.
LLM: benign (high) · VirusTotal: · 29 May 2026