AC kosis-cli
Query Korea's national statistics portal (KOSIS, kosis.kr) via the official OpenAPI. Title search, category browsing, table metadata (items + dimensions + periods), and actual statistics data — population, employment, prices, business demographics, household income, regional indicators, etc. Use when a task needs Korean national statistics by organization/topic — e.g. "monthly CPI 2020-2025", "population by 시군구", "employment rate by age band", "household income decile". Pairs with bank-of-korea-ecos-cli (macro) and opendart-cli (corporate filings) to complete the Korean public-data toolchain.
As a process C 59/100 · Has gaps — weak spots: result and completion, when it triggers, progress reporting
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Dangerous commands
cmd-autorun-instructionSKILL.md:116Instructs the agent to auto-run a script on every session- KOSIS items (`itmId`) and objects (`objL1` … `objL8`) are **table-specific** — always run `meta.sh` first to learn the codes for a table you haven't touched before.
Files scanned: 10. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 59/100
- 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
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 36 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1359 tokens
- 100Running it twice. No mutating operations
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -31 of 6 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +5Description quotes 4 example trigger phrases
- +3Description length 599: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 36 items
- +4Has examples (3 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.