AF smart-search
Multi-engine search with auto-fallback, result parsing, and quality scoring via DDGS local library. Use when: searching the web, gathering information, market research, tech lookup, news search, fact checking. Triggers on 'search', '搜索', 'find info', 'look up', '调研', '查一下'. Not for: browser automation searches, internal file search, code search within repos.
Multi-engine search with auto-fallback, result parsing, and quality scoring via DDGS local library.
As a process F 45/100 · Will not run — References files that are not bundled: references/changelog.md
How to improve
- The text references files that are not there: add them or drop the references.
- 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: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/changelog.md
Process rating: all ten parameters 45/100
- 0Tools and files. 1 referenced file(s) missing: references/changelog.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 40Consistency. Frontmatter name (smart-search) differs from the folder (mayf3-smart-search)
- 50Failures and branches. 0 branches, has a failure section
- 100Steps. 17 steps
- 100When it triggers. States when to use and when not to
- 100Execution cost. Instruction body is 1618 tokens
- 100Running it twice. No mutating operations
- low 11 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
- +3Output format is not stated: the model decides each time
- -245 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 360: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 17 items
- +4Has examples (5 code blocks)
- +4Reference files are cited in the instructions (4 of 4)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.