BC yahooquery
Access Yahoo Finance data including real-time pricing, fundamentals, analyst estimates, options, news, and historical data via the yahooquery Python library.
Access Yahoo Finance data including real-time pricing, fundamentals, analyst estimates, options, news, and historical data via the yahooquery Python library.
As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 3
✓ No critical or high findings
Medium and low: 3
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low Secrets in code
secret-high-entropy-tokenreferences/research.md:183High-entropy token-like string (may be an id, hash or a credential)| 0 | 2020…00Z | Short term | BHLB | Sell | 8.3 | -0.177134 | tc_U…CIg | https://s.yimg.com/uc/fin/img/bearish-continuation-wedge.svg
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low Secrets in code
secret-high-entropy-tokenreferences/research.md:184High-entropy token-like string (may be an id, hash or a credential)| 1 | 2020…00Z | Short term | FISV | Buy | 107.82 | 0.070492 | tc_U…CJg | https://s.yimg.com/uc/fin/img/bullish-double-bottom.svg
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low Secrets in code
secret-high-entropy-tokenreferences/ticker/modules.md:2425High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)"pric…ths": 6.223116,
quoted
Files scanned: 14. 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")
Process rating: all ten parameters 54/100
- 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
- 20When it triggers. No condition that starts the skill
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 85Steps. 65 steps, 1 vague phrases
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2146 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
- +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
- -4Absolute local paths (C:\Users, /home/…): not portable
- +1No license
- +2Single-language instructions
- +3Description length 157: enough signal without eating the budget
- +4Structure: 34 headings
- +3Step-by-step instructions: 65 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (6 of 6)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.