AC yahoo-network-research
Researches Yahoo's editorial content network — Autos, Entertainment, Health, Life, News, Shopping, Sports, and Tech — via the Crawlora API, returning clean JSON. Each vertical shares a home/category story-stream plus full-article-content pattern; Yahoo Sports adds deeper sports-data endpoints (scoreboards, standings, team/player/roster, golf, MMA, motorsports, tennis, Olympics). Use when the user wants a Yahoo section's story feed, a Yahoo article's full content, Yahoo News comments, Yahoo Shopping deals/lists, or Yahoo Sports scores/standings/schedules. Yahoo Finance and Yahoo Search are covered by their own separate skills, not this one.
Researches Yahoo's editorial content network — Autos, Entertainment, Health, Life, News, Shopping, Sports, and Tech — via the Crawlora API, returning clean…
As a process C 58/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches
The same skill appears in 1 more place: ClawHub
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 · 2
✓ No critical or high findings
Medium and low: 2
-
low Exfiltration
net-credential-usescripts/crawlora.sh:16Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host; quoted — discussed, not commanded): "${CRAWLORA_API_KEY:?Set CRAWLORA_API_KEY first — get a free key at https://crawlora.net?utm_source=…&utm_medium=…&utm_campaign=…"vendor-hostquoted -
low Exfiltration
net-credential-usescripts/crawlora.sh:118Credential used in a network call (verify the destination is the intended service) (quoted — discussed, not commanded)printf 'header = "x-api-key: %s"\n' "$CRAWLORA_API_KEY" >"$curl_config"
quoted
Files scanned: 4. 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 58/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 5 mutating operations with no state check
- 85Steps. 33 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100When it triggers. States when to use and when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2088 tokens
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
- +1No license
- +2Single-language instructions
- +3Description length 647: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 33 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.