BC smart-search
Intelligent web search routing across Gemini and Brave APIs with quota management, circuit breaker, and web_fetch fallback. Routes finance queries to Gemini, space/astronomy to Brave, with per-agent daily allocations and shared pool.
As a process C 57/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
ProcedureSales and CRMInfrastructureAI and agentstype and topics are labelled automatically from the skill text
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: 13. 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 "homepage"
Process rating: all ten parameters 57/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 2 mutating operations with no state check
- 40Consistency. Frontmatter name (smart-search) differs from the folder (aira-smart-search)
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 6 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Execution cost. Instruction body is 3796 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 13 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
- -42 reference files, but SKILL.md never points to them: the model will not open them
- -32 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 233: enough signal without eating the budget
- +4Structure: 25 headings
- +3Step-by-step instructions: 6 items
- +4Has examples (17 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.
External checks
ClawHub: clean
This is a disclosed web-search routing skill that sends queries to search providers and keeps local search logs, so it is privacy-sensitive but not deceptive or purpose-mismatched.
LLM: benign (high) · VirusTotal: · 29 May 2026