AF fia-signals
AI crypto market intelligence from Fía Signals. 65+ endpoints covering price predictions, technical analysis (RSI MACD EMA Bollinger), market sentiment, smart money tracking, DeFi yield rates, gas prices (14 chains), Solana trending tokens, MEV detection, wallet risk scoring, on-chain data, crypto signals, trading signals, regime detection, funding rates, VIRTUAL token analysis, smart contract auditing. Free tier — no API key. Use when asked about: crypto market data, price prediction, technical analysis, gas prices, Solana trending tokens, DeFi yields, MEV bots, smart contract audit, wallet risk, research topics, BTC due diligence, smart money tracking, whale activity, market sentiment, trading signals, regime detection, on-chain analytics, funding rates, crypto analysis.
As a process F 34/100 · Will not run — weak spots: steps, result and completion, when it triggers
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 Secrets in code
secret-high-entropy-tokenREADME.md:170High-entropy token-like string (may be an id, hash or a credential) (documentation table row)| Wallet | `0x3c…3Bf` |
table
Files scanned: 5. 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 34/100
- 0Steps. Prose only: no discrete steps
- 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
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (fia-signals) differs from the folder (fia-signals-skill)
- 100Tools and files. No external tools needed
- 100Execution cost. Instruction body is 733 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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 783: enough signal without eating the budget
- +4Structure: 6 headings
- +4Has examples (1 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.