AB game-scout
Video game strategy specialist. Amalgamates tactics, builds, guides, and meta knowledge from Reddit, YouTube creators, wikis, Twitter/X, and game databases to unlock a higher gaming experience. Trigger on: builds, loadouts, tier lists, meta, strategy, "best build for", "what's meta in", "how to play", "is X still good", "what does X do", patch notes, weapon stats, item guides, pro play, or any question mentioning a video game by name.
As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, running it twice, progress reporting
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
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low Exfiltration
net-credential-usescripts/bright-twitter.mjs:82Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)console.error(`Check later: curl -H "Authorization: Bearer $BRIGHTDATA_API_KEY" "https://api.brightdata.com/datasets/v3/snapshot/${snapshot_id}?format=json"`);quoted
Files scanned: 13. 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 68/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (web, python, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Steps. 42 steps
- 100Failures and branches. 6 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2492 tokens
- low The response is described with custom markup (4 tags): a typed call is more reliable
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)
- +1No license
- +2Single-language instructions
- +5Description quotes 5 example trigger phrases
- +3Description length 438: enough signal without eating the budget
- +4Structure: 24 headings
- +3Step-by-step instructions: 42 items
- +3Output format is stated explicitly
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +3All 6 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 99.